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314 full-text articles. Page 1 of 12.

Predicting Unplanned Medical Visits Among Patients With Diabetes Using Machine Learning, Arielle Selya, Eric L. Johnson 2019 Sanford Health

Predicting Unplanned Medical Visits Among Patients With Diabetes Using Machine Learning, Arielle Selya, Eric L. Johnson

SDSU Data Science Symposium

Diabetes poses a variety of medical complications to patients, resulting in a high rate of unplanned medical visits, which are costly to patients and healthcare providers alike. However, unplanned medical visits by their nature are very difficult to predict. The current project draws upon electronic health records (EMR’s) of adult patients with diabetes who received care at Sanford Health between 2014 and 2017. Various machine learning methods were used to predict which patients have had an unplanned medical visit based on a variety of EMR variables (age, BMI, blood pressure, # of prescriptions, # of diagnoses on problem list, A1C, HDL ...


Innate Immunity, The Hepatic Extracellular Matrix, And Liver Injury: Mathematical Modeling Of Metastatic Potential And Tumor Development In Alcoholic Liver Disease., Shanice V. Hudson 2018 University of Louisville

Innate Immunity, The Hepatic Extracellular Matrix, And Liver Injury: Mathematical Modeling Of Metastatic Potential And Tumor Development In Alcoholic Liver Disease., Shanice V. Hudson

Electronic Theses and Dissertations

The overarching goals of the current work are to fill key gaps in the current understanding of alcohol consumption and the risk of metastasis to the liver. Considering the evidence this research group has compiled confirming that the hepatic matrisome responds dynamically to injury, an altered extracellular matrix (ECM) profile appears to be a key feature of pre-fibrotic inflammatory injury in the liver. This group has demonstrated that the hepatic ECM responds dynamically to alcohol exposure, in particular, sensitizing the liver to LPS-induced inflammatory damage. Although the study of alcohol in its role as a contributing factor to oncogenesis and ...


Estimators Comparison Of Separable Covariance Structure With One Component As Compound Symmetry Matrix, Katarzyna Filipiak, Daniel Klein, Monika Mokrzycka 2018 Poznan University of Technology

Estimators Comparison Of Separable Covariance Structure With One Component As Compound Symmetry Matrix, Katarzyna Filipiak, Daniel Klein, Monika Mokrzycka

Electronic Journal of Linear Algebra

The maximum likelihood estimation (MLE) of separable covariance structure with one component as compound symmetry matrix has been widely studied in the literature. Nevertheless, the proposed estimates are not given in explicit form and can be determined only numerically. In this paper we give an alternative form of MLE and we show that this new algorithm is much quicker than the algorithms given in the literature.\\ Another estimator of covariance structure can be found by minimizing the entropy loss function. In this paper we give three methods of finding the best approximation of separable covariance structure with one component as ...


41 - Data Exploration And Analysis For The Hemingway Measure Of Adult Connectedness, Gildardo Bautista-Maya, Ping Ye, Diane Cook 2018 University of North Georgia

41 - Data Exploration And Analysis For The Hemingway Measure Of Adult Connectedness, Gildardo Bautista-Maya, Ping Ye, Diane Cook

Georgia Undergraduate Research Conference (GURC)

Abstract:

We analyze the dataset collected from students participating in the Boy With A Ball (BWAB) program, a faith-based community outreach group, through the Hemingway Measure of Adult Connectedness©, a questionnaire measuring the social connectedness of adolescents. First, we approach the data in the conventional method provided by the Hemingway website. We then identify which questions are strong determiners in deciding whether a student has completed the BWAB program or not. With the goal of utilizing the logistic regression, we reduce the set of questions to those only identified as significant in other methods. These methods include linear regression, decision ...


On Projection Of A Positive Definite Matrix On A Cone Of Nonnegative Definite Toeplitz Matrices, Katarzyna Filipiak, Augustyn Markiewicz, Adam Mieldzioc, Aneta Sawikowska 2018 Poznań University Of Technology

On Projection Of A Positive Definite Matrix On A Cone Of Nonnegative Definite Toeplitz Matrices, Katarzyna Filipiak, Augustyn Markiewicz, Adam Mieldzioc, Aneta Sawikowska

Electronic Journal of Linear Algebra

We consider approximation of a given positive definite matrix by nonnegative definite banded Toeplitz matrices. We show that the projection on linear space of Toeplitz matrices does not always preserve nonnegative definiteness. Therefore we characterize a convex cone of nonnegative definite banded Toeplitz matrices which depends on the matrix dimensions, and we show that the condition of positive definiteness given by Parter [{\em Numer. Math. 4}, 293--295, 1962] characterizes the asymptotic cone. In this paper we give methodology and numerical algorithm of the projection basing on the properties of a cone of nonnegative definite Toeplitz matrices. This problem can be ...


Estimating And Correcting Interference Fringes In Infrared Spectra In Infrared Hyperspectral Imaging, Ghazal Azarfar, Ebrahim Aboualizadeh, Nicholas Walter,, Simona Ratti, Camilla Olivieri, Alessandra Alessandra, Michael Nasse, Achim Kohler, Mario Giordano, Carol Hirschmugl 2018 University of Wisconsin Milwaukee

Estimating And Correcting Interference Fringes In Infrared Spectra In Infrared Hyperspectral Imaging, Ghazal Azarfar, Ebrahim Aboualizadeh, Nicholas Walter,, Simona Ratti, Camilla Olivieri, Alessandra Alessandra, Michael Nasse, Achim Kohler, Mario Giordano, Carol Hirschmugl

Physics Faculty Articles

Short-term acclimation response of individual cells of Thalassiosira weissflogii was monitored by Synchrotron FTIR imaging over the span of 75 minutes. The cells, collected from batch cultures, were maintained in a constant flow of medium, at an irradiance of 120 μmol m−2 s−1 and at 20 °C. Multiple internal reflections due to the micro fluidic channel were modeled, and showed that fringes are additive sinusoids to the pure absorption of the other components of the system. Preprocessing of the hyperspectral cube (x, y, Abs(λ)) included removing spectral fringe using an EMSC approach. Principal component analysis of the ...


The Periglacial Landscape Of Mars: Insight Into The 'Decameter-Scale Rimmed Depressions' In Utopia Planitia, Arya Bina 2018 The University of Western Ontario

The Periglacial Landscape Of Mars: Insight Into The 'Decameter-Scale Rimmed Depressions' In Utopia Planitia, Arya Bina

Electronic Thesis and Dissertation Repository

Currently, Mars appears to be in a ‘frozen’ and ‘dry’ state, with the clear majority of the planet’s surface maintaining year-round sub-zero temperatures. However, the discovery of features consistent with landforms found in periglacial environments on Earth, suggests a climate history for Mars that may have involved freeze and thaw cycles. Such landforms include hummocky, polygonised, scalloped, and pitted terrains, as well as ice-rich deposits and gullies, along the mid- to high-latitude bands, typically with no lower than 20o N/S. The detection of near-surface and surface ice via the Phoenix lander, excavation of ice via recent impact cratering ...


Yelp’S Review Filtering Algorithm, Yao Yao, Ivelin Angelov, Jack Rasmus-Vorrath, Mooyoung Lee, Daniel W. Engels 2018 Southern Methodist University

Yelp’S Review Filtering Algorithm, Yao Yao, Ivelin Angelov, Jack Rasmus-Vorrath, Mooyoung Lee, Daniel W. Engels

SMU Data Science Review

In this paper, we present an analysis of features influencing Yelp's proprietary review filtering algorithm. Classifying or misclassifying reviews as recommended or non-recommended affects average ratings, consumer decisions, and ultimately, business revenue. Our analysis involves systematically sampling and scraping Yelp restaurant reviews. Features are extracted from review metadata and engineered from metrics and scores generated using text classifiers and sentiment analysis. The coefficients of a multivariate logistic regression model were interpreted as quantifications of the relative importance of features in classifying reviews as recommended or non-recommended. The model classified review recommendations with an accuracy of 78%. We found that ...


Testing Hypotheses Of Covariance Structure In Multivariate Data, Miguel Fonseca, Arkadiusz Koziol, Roman Zmyslony 2018 NOVA University of Lisbon

Testing Hypotheses Of Covariance Structure In Multivariate Data, Miguel Fonseca, Arkadiusz Koziol, Roman Zmyslony

Electronic Journal of Linear Algebra

In this paper there is given a new approach for testing hypotheses on the structure of covariance matrices in double multivariate data. It is proved that ratio of positive and negative parts of best unbiased estimators (BUE) provide an F-test for independence of blocks variables in double multivariate models.


Application Of Jordan Algebra For Testing Hypotheses About Structure Of Mean Vector In Model With Block Compound Symmetric Covariance Structure, Roman Zmyślony, Ivan Zezula, Arkadiusz Kozioł 2018 Faculty of Mathematics, Computer Science and Econometrics, University of Zielona Góra,

Application Of Jordan Algebra For Testing Hypotheses About Structure Of Mean Vector In Model With Block Compound Symmetric Covariance Structure, Roman Zmyślony, Ivan Zezula, Arkadiusz Kozioł

Electronic Journal of Linear Algebra

In this article authors derive test for structure of mean vector in model with block compound symmetric covariance structure for two-level multivariate observations. One possible structure is so called structured mean vector when its components remain constant over sites or over time points, so that mean vector is of the form $\boldsymbol{1}_{u}\otimes\boldsymbol{\mu}$ with $\boldsymbol{\mu}=(\mu_1,\mu_2,\ldots,\mu_m)'\in\mathbb{R}^m$. This hypothesis is tested against alternative of unstructured mean vector, which can change over sites or over time points.


Scale-Invariant Geometric Data Analysis (Sigda), Marina Girgis, Max Robinson 2018 Cal Poly Pomona (CPP)

Scale-Invariant Geometric Data Analysis (Sigda), Marina Girgis, Max Robinson

STAR (STEM Teacher and Researcher) Presentations

The purpose of this research is to introduce a new data analysis method called Scale Invariant Geometric Data Analysis (SIGDA). SIGDA has been shown to be more informative than more common data analysis methods, such as Principal Component Analysis (PCA). SIGDA is used to visualize complex data sets in a way that accurately preserves data patterns and behavior. SIGDA is designed to preserve relative ratios in a numerical matrix, and the number of entries has to be more than the total number of rows and columns. Our research involved providing a simple explanation of SIGDA's mathematical process—simple enough ...


Pretrial Release And Failure-To-Appear In Mclean County, Il, Jonathan Monsma 2018 Illinois State University

Pretrial Release And Failure-To-Appear In Mclean County, Il, Jonathan Monsma

Stevenson Center for Community and Economic Development to Stevenson Center for Community and Economic Development—Student Research

Actuarial risk assessment tools increasingly have been employed in jurisdictions across the U.S. to assist courts in the decision of whether someone charged with a crime should be detained or released prior to their trial. These tools should be continually monitored and researched by independent 3rd parties to ensure that these powerful tools are being administered properly and used in the most proficient way as to provide socially optimal results. McLean County, Illinois began using the Public Safety Assessment-CourtTM (PSA-Court or simply PSA) risk assessment tool beginning in 2016. This study culls data from the McLean County ...


Quantitative Electroencephalography For Detecting Concussions, Sara Krehbiel, Kathy Hoke, Joanna Wares 2018 University of Richmond

Quantitative Electroencephalography For Detecting Concussions, Sara Krehbiel, Kathy Hoke, Joanna Wares

Biology and Medicine Through Mathematics Conference

No abstract provided.


A 3d Characteristics Database Of Land Engraved Areas With Known Subclass, EnTni Lin 2018 City University of New York (CUNY)

A 3d Characteristics Database Of Land Engraved Areas With Known Subclass, Entni Lin

Student Theses

Subclass characteristics on bullets may mislead firearm examiners when they rely on traditional 2D images. In order to provide indelible examples for training and help avoid identification errors, 3D topography surface maps and statistical methods of pattern recognition are applied to toolmarks on bullets containing known subclass characteristics. This research was conducted by collecting 3D topography surface map data from land engraved areas of bullets fired through known barrels. This data was processed and used to train the statistical algorithms to predict their origin. The results from the algorithm are compared with the “right answers” (i.e. correct IDs) of ...


The Use Of Elemental Databases In Forensic Science: Studies On Vehicle Glass Interpretation And Milk Powder Provenancing, Tricia Marie Hoffman 2018 Florida International University

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% confidence ...


Fast Identification Of Components Commonly Used In Homemade Explosives By Spectroscopic And Chemometric Methods, Deidre Day Vandenbos, Huggins Msimanga, Christopher Dockery 2018 Kennesaw State University

Fast Identification Of Components Commonly Used In Homemade Explosives By Spectroscopic And Chemometric Methods, Deidre Day Vandenbos, Huggins Msimanga, Christopher Dockery

Master of Science in Chemical Sciences Theses

Homemade explosives (HMEs) have become a global pandemic. This forensic research focuses on developing identification methods that can provide quick, cost effective, non-destructive analysis using portable instrumentation. These capabilities would be invaluable to first responders, military, and security officials to establish an evidentiary link between a suspect and a reference in cases of HMEs, IEDs, arson and environmental contamination.

Modern methods for quick identification of the fuels and oxidant sources used in manufacturing HMEs, include Fourier Transform Infrared (FT-IR) and Raman spectroscopy. Visual confirmation alone, however, is not strong enough to discriminate chemicals with nearly identical spectra, which occurs when ...


Analysis Of 2016-17 Major League Soccer Season Data Using Poisson Regression With R, ian d. campbell 2018 Lynchburg College

Analysis Of 2016-17 Major League Soccer Season Data Using Poisson Regression With R, Ian D. Campbell

Undergraduate Theses and Capstone Projects

To the outside observer, soccer is chaotic with no given pattern or scheme to follow, a random conglomeration of passes and shots that go on for 90 minutes. Yet, what if there was a pattern to the chaos, or a way to describe the events that occur in the game quantifiably. Sports statistics is a critical part of baseball and a variety of other of today’s sports, but we see very little statistics and data analysis done on soccer. Of this research, there has been looks into the effect of possession time on the outcome of a game, the ...


Longitudinal Tracking Of Physiological State With Electromyographic Signals., Robert Warren Stallard 2018 University of Louisville

Longitudinal Tracking Of Physiological State With Electromyographic Signals., Robert Warren Stallard

Electronic Theses and Dissertations

Electrophysiological measurements have been used in recent history to classify instantaneous physiological configurations, e.g., hand gestures. This work investigates the feasibility of working with changes in physiological configurations over time (i.e., longitudinally) using a variety of algorithms from the machine learning domain. We demonstrate a high degree of classification accuracy for a binary classification problem derived from electromyography measurements before and after a 35-day bedrest. The problem difficulty is increased with a more dynamic experiment testing for changes in astronaut sensorimotor performance by taking electromyography and force plate measurements before, during, and after a jump from a small ...


Chemical And Statistical Analysis Of Karst Groundwater Basin Signatures - Springfield, Mo, Benjamin E. Lockwood 2018 Missouri State University

Chemical And Statistical Analysis Of Karst Groundwater Basin Signatures - Springfield, Mo, Benjamin E. Lockwood

MSU Graduate Theses

Springfield, MO is located on the Springfield Plateau physiographic province. The Springfield plateau contains a number of Mississippian aged units and is mainly capped by the Burlington-Keokuk Formation. The Burlington-Keokuk is a highly fossiliferous limestone with nodular and interbedded chert. Beneath the Burlington-Keokuk lies the Elsey, Reeds Spring, and Pierson Formations respectively which comprise the Springfield Plateau aquifer hydrostratigraphic unit. Within the Springfield Plateau aquifer, a well-developed karst system includes springs, sinkholes, and caves. The Springfield Plateau aquifer is the predominant source for springs and seeps in the Springfield area. The purpose of this study was to understand the differences ...


Analysis Challenges For High Dimensional Data, Bangxin Zhao 2018 The University of Western Ontario

Analysis Challenges For High Dimensional Data, Bangxin Zhao

Electronic Thesis and Dissertation Repository

In this thesis, we propose new methodologies targeting the areas of high-dimensional variable screening, influence measure and post-selection inference. We propose a new estimator for the correlation between the response and high-dimensional predictor variables, and based on the estimator we develop a new screening technique termed Dynamic Tilted Current Correlation Screening (DTCCS) for high dimensional variables screening. DTCCS is capable of picking up the relevant predictor variables within a finite number of steps. The DTCCS method takes the popular used sure independent screening (SIS) method and the high-dimensional ordinary least squares projection (HOLP) approach as its special cases.

Two methods ...


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