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Articles 1 - 12 of 12
Full-Text Articles in Multivariate Analysis
A Bayesian Programming Approach To Car-Following Model Calibration And Validation Using Limited Data, Franklin Abodo
A Bayesian Programming Approach To Car-Following Model Calibration And Validation Using Limited Data, Franklin Abodo
FIU Electronic Theses and Dissertations
Traffic simulation software is used by transportation researchers and engineers to design and evaluate changes to roadway networks. Underlying these simulators are mathematical models of microscopic driver behavior from which macroscopic measures of flow and congestion can be recovered. Many models are intended to apply to only a subset of possible traffic scenarios and roadway configurations, while others do not have any explicit constraint on their applicability. Work zones on highways are one scenario for which no model invented to date has been shown to accurately reproduce realistic driving behavior. This makes it difficult to optimize for safety and other …
Integrating Compound Flood Conditions Through 2d Hydraulic Modeling For Simulating Flood Risk Processes In Coastal Cities, Francisco Pena Guerra Mr.
Integrating Compound Flood Conditions Through 2d Hydraulic Modeling For Simulating Flood Risk Processes In Coastal Cities, Francisco Pena Guerra Mr.
FIU Electronic Theses and Dissertations
Low elevation coastal karst environments are highly vulnerable to flooding conditions due to climate change. Trends in rising global temperatures have increased the frequency and intensity of extreme precipitation, hydrometeorological phenomena and sea level rise, exacerbating the impact of pluvial, fluvial, coastal and groundwater flood hazards. Compound flooding events amplify flood hazards and pose a higher threat to residents and infrastructure in unison compared to independent phenomena. Recent advancements in coupling hydrologic and hydraulic modeling frameworks have improved our ability to account for the combined effects of extreme pluvial, fluvial, and coastal flood hazards. This innovation in the hydroinformatics field …
Development Of A Dna Methylation Multiplex Assay For Body Fluid Identification And Age Determination, Quentin Gauthier
Development Of A Dna Methylation Multiplex Assay For Body Fluid Identification And Age Determination, Quentin Gauthier
FIU Electronic Theses and Dissertations
For forensic laboratories, the determination of body fluid origin of samples collected at a crime scene are typically presumptive and often destructive. However, given that in certain cases the presence of DNA is not in dispute and rather where the DNA came from is of primary concern, new methodologies are needed. Epigenetic modifications, such as DNA methylation, affect gene expression in every cell of every mammal. These DNA methylation patterns typically are observed as the addition of a methyl group on the 5’ carbon of a cytosine followed by guanine (CpG). Methylation patterns have been observed to change in response …
Development Of Gaussian Learning Algorithms For Early Detection Of Alzheimer's Disease, Chen Fang
Development Of Gaussian Learning Algorithms For Early Detection Of Alzheimer's Disease, Chen Fang
FIU Electronic Theses and Dissertations
Alzheimer’s disease (AD) is the most common form of dementia affecting 10% of the population over the age of 65 and the growing costs in managing AD are estimated to be $259 billion, according to data reported in the 2017 by the Alzheimer's Association. Moreover, with cognitive decline, daily life of the affected persons and their families are severely impacted. Taking advantage of the diagnosis of AD and its prodromal stage of mild cognitive impairment (MCI), an early treatment may help patients preserve the quality of life and slow the progression of the disease, even though the underlying disease cannot …
Best Probable Subset: A New Method For Reducing Data Dimensionality In Linear Regression, Elieser Nodarse
Best Probable Subset: A New Method For Reducing Data Dimensionality In Linear Regression, Elieser Nodarse
FIU Electronic Theses and Dissertations
Regression is a statistical technique for modeling the relationship between a dependent variable Y and two or more predictor variables, also known as regressors. In the broad field of regression, there exists a special case in which the relationship between the dependent variable and the regressor(s) is linear. This is known as linear regression.
The purpose of this paper is to create a useful method that effectively selects a subset of regressors when dealing with high dimensional data and/or collinearity in linear regression. As the name depicts it, high dimensional data occurs when the number of predictor variables is far …
The Use Of Elemental Databases In Forensic Science: Studies On Vehicle Glass Interpretation And Milk Powder Provenancing, Tricia Marie Hoffman
The Use Of Elemental Databases In Forensic Science: Studies On Vehicle Glass Interpretation And Milk Powder Provenancing, Tricia Marie Hoffman
FIU Electronic Theses and Dissertations
The first study focuses on the development of a laser based method for the elemental analysis of solid milk powder. Milk powder samples originating from five different countries were analyzed to determine any geographic differences. A LA-ICP-MS method was developed and compared to k0-INAA for several milk samples as well as a reference sample. Precision of 10% RSD or better and a bias of 10% was achieved for both techniques for most elements with LA-ICP-MS producing lower limits of detection (~ 1 ppm) for Sr. The comparison of LA-ICP-MS to k0-INAA showed overlap of the 95% …
An Investigation Of The Effects Of Taking Remedial Math In College On Degree Attainment And College Gpa Using Multiple Imputation And Propensity Score Matching, Meghan A. Clovis
An Investigation Of The Effects Of Taking Remedial Math In College On Degree Attainment And College Gpa Using Multiple Imputation And Propensity Score Matching, Meghan A. Clovis
FIU Electronic Theses and Dissertations
Enrollment in degree-granting postsecondary institutions in the U.S. is increasing, as are the numbers of students entering academically underprepared. Students in remedial mathematics represent the largest percentage of total enrollment in remedial courses, and national statistics indicate that less than half of these students pass all of the remedial math courses in which they enroll. In response to the low pass rates, numerous studies have been conducted into the use of alternative modes of instruction to increase passing rates. Despite myriad studies into course redesign, passing rates have seen no large-scale improvement. Lacking is a thorough investigation into preexisting differences …
On The Performance Of Some Poisson Ridge Regression Estimators, Cynthia Zaldivar
On The Performance Of Some Poisson Ridge Regression Estimators, Cynthia Zaldivar
FIU Electronic Theses and Dissertations
Multiple regression models play an important role in analyzing and making predictions about data. Prediction accuracy becomes lower when two or more explanatory variables in the model are highly correlated. One solution is to use ridge regression. The purpose of this thesis is to study the performance of available ridge regression estimators for Poisson regression models in the presence of moderately to highly correlated variables. As performance criteria, we use mean square error (MSE), mean absolute percentage error (MAPE), and percentage of times the maximum likelihood (ML) estimator produces a higher MSE than the ridge regression estimator. A Monte Carlo …
The Interactions Of Relationships, Interest, And Self-Efficacy In Undergraduate Physics, Remy Dou
The Interactions Of Relationships, Interest, And Self-Efficacy In Undergraduate Physics, Remy Dou
FIU Electronic Theses and Dissertations
This collected papers dissertation explores students’ academic interactions in an active learning, introductory physics settings as they relate to the development of physics self-efficacy and interest. The motivation for this work extends from the national call to increase participation of students in the pursuit of science, technology, engineering, and mathematics (STEM) careers. Self-efficacy and interest are factors that play prominent roles in popular, evidence-based, career theories, including the Social cognitive career theory (SCCT) and the identity framework. Understanding how these constructs develop in light of the most pervasive characteristic of the active learning introductory physics classroom (i.e., peer-to-peer interactions) has …
Biogeographical Patterns Of Soil Microbial Communities: Ecological, Structural, And Functional Diversity And Their Application To Soil Provenance, Natalie Damaso
FIU Electronic Theses and Dissertations
The current ecological hypothesis states that the soil type (e.g., chemical and physical properties) determines which microbes occupy a particular soil and provides the foundation for soil provenance studies. As human profiles are used to determine a match between evidence from a crime scene and a suspect, a soil microbial profile can be used to determine a match between soil found on the suspect’s shoes or clothing to the soil at a crime scene. However, for a robust tool to be applied in forensic application, an understanding of the uncertainty associated with any comparisons and the parameters that can significantly …
Gis-Integrated Mathematical Modeling Of Social Phenomena At Macro- And Micro- Levels—A Multivariate Geographically-Weighted Regression Model For Identifying Locations Vulnerable To Hosting Terrorist Safe-Houses: France As Case Study, Elyktra Eisman
FIU Electronic Theses and Dissertations
Adaptability and invisibility are hallmarks of modern terrorism, and keeping pace with its dynamic nature presents a serious challenge for societies throughout the world. Innovations in computer science have incorporated applied mathematics to develop a wide array of predictive models to support the variety of approaches to counterterrorism. Predictive models are usually designed to forecast the location of attacks. Although this may protect individual structures or locations, it does not reduce the threat—it merely changes the target. While predictive models dedicated to events or social relationships receive much attention where the mathematical and social science communities intersect, models dedicated to …
A Study On The Correlation Of Bivariate And Trivariate Normal Models, Maria Del Pilar Orjuela
A Study On The Correlation Of Bivariate And Trivariate Normal Models, Maria Del Pilar Orjuela
FIU Electronic Theses and Dissertations
Suppose two or more variables are jointly normally distributed. If there is a common relationship between these variables it would be very important to quantify this relationship by a parameter called the correlation coefficient which measures its strength, and the use of it can develop an equation for predicting, and ultimately draw testable conclusion about the parent population.
This research focused on the correlation coefficient ρ for the bivariate and trivariate normal distribution when equal variances and equal covariances are considered. Particularly, we derived the maximum Likelihood Estimators (MLE) of the distribution parameters assuming all of them are unknown, and …