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Full-Text Articles in Physical Sciences and Mathematics

The Impact Of Fe-Ti Oxide Concentration On The Structural Ridgity Of The Lower Oceanic Crust, Atlantis Bank, Southwest Indian Ridge, Daniel Winkler Dec 2017

The Impact Of Fe-Ti Oxide Concentration On The Structural Ridgity Of The Lower Oceanic Crust, Atlantis Bank, Southwest Indian Ridge, Daniel Winkler

Master's Theses

Fe-Ti oxides are important components of oceanic core complexes (OCC) formed at slow-spreading mid-ocean ridges since Fe-Ti oxides are more susceptible to crystal-plastic deformation than silicate minerals. This study investigated the predicted relationship between the presence and concentration of Fe-Ti oxides and the presence and intensity of crystal-plastic deformation in gabbroic samples from Atlantis Bank, Southwest Indian Ridge (SWIR). Atlantis Bank is an oceanic core complex that formed through the exhumation of lower oceanic crust along a detachment fault. OCCs form along slow-spreading ridges and are characterized by the complex interactions between magmatism and lithospheric extension, thus making these complexes …


Anomalydetection: Implementation Of Augmented Network Log Anomaly Detection Procedures, Robert J. Gutierrez, Bradley C. Boehmke, Kenneth W. Bauer, Cade M. Saie, Trevor J. Bihl Aug 2017

Anomalydetection: Implementation Of Augmented Network Log Anomaly Detection Procedures, Robert J. Gutierrez, Bradley C. Boehmke, Kenneth W. Bauer, Cade M. Saie, Trevor J. Bihl

Faculty Publications

As the number of cyber-attacks continues to grow on a daily basis, so does the delay in threat detection. For instance, in 2015, the Office of Personnel Management discovered that approximately 21.5 million individual records of Federal employees and contractors had been stolen. On average, the time between an attack and its discovery is more than 200 days. In the case of the OPM breach, the attack had been going on for almost a year. Currently, cyber analysts inspect numerous potential incidents on a daily basis, but have neither the time nor the resources available to perform such a task. …


Visualizing Lab And Phenotype Associations Using Phewas And Electronic Health Records, Brenda Emerson, Miriam Goldman, Sahiti Kolli Jul 2017

Visualizing Lab And Phenotype Associations Using Phewas And Electronic Health Records, Brenda Emerson, Miriam Goldman, Sahiti Kolli

Honors Projects

As the digitization of patient health records is becoming more common, we are given a great opportunity to analyze these records and hopefully make discoveries about diseases or medicines. Being given large datasets of Electronic Health Records, I and two other students decided to look for novel phenotype associations with mean lab values, look to see whether the presence of a lab had associations with a phenotype, and create an interactive application to visual the associations between labs and phenotypes.


Comparing Baseball Players Using Expected Runs In Shiny, Spencer Rodrigues Jun 2017

Comparing Baseball Players Using Expected Runs In Shiny, Spencer Rodrigues

Statistics

No abstract provided.


Jmasm43: Teereg: Trimmed Elemental Estimation (R), Wei Jiang, Matthew S. Mayo May 2017

Jmasm43: Teereg: Trimmed Elemental Estimation (R), Wei Jiang, Matthew S. Mayo

Journal of Modern Applied Statistical Methods

Trimmed elemental regression is robust to outliers and violations of model assumptions. Its properties and statistical inference were evaluated using bias-corrected and accelerated bootstrap confidence intervals. An R package named TEEReg is developed to compute the trimmed elemental estimates and the corresponding bootstrap confidence intervals. Two examples are provided to demonstrate its usage.


Selection Of Statistical Software For Data Scientists And Teachers, Ceyhun Ozgur, Min Dou, Yang Li, Grace Rogers May 2017

Selection Of Statistical Software For Data Scientists And Teachers, Ceyhun Ozgur, Min Dou, Yang Li, Grace Rogers

Journal of Modern Applied Statistical Methods

The need for analysts with expertise in big data software is becoming more apparent in today’s society. Unfortunately, the demand for these analysts far exceeds the number available. A potential way to combat this shortage is to identify the software sought by employers and to align this with the software taught by universities. This paper will examine multiple data analysis software – Excel add-ins, SPSS, SAS, Minitab, and R – and it will outline the cost, training, statistical methods/tests/uses, and specific uses within industry for each of these software. It will further explain implications for universities and students.