Engineering Commons^™

Performance Of Lambda@Edge Vs. Lambda Environment, Sam Dotson, Wei Hao

Posters-at-the-Capitol

Abstract

The purpose of this research has been to observe how performance of the Lambda@EDGE environment compares to the base Lambda environment. This is in an effort to determine viability of the EDGE environment. 15 tests were conducted over a matter of days in each environment whereby the Fibonacci sequence was calculated to 20 terms. Performance metrics including RAM usage and response time were measured. Lambda@EDGE was determined to have not only a slightly higher average response time but also an average RAM usage of 1MB more in the aggregate tests.

Understanding The Privacy Methods, Implications, And Challenges Of Educational Data Mining., Tyler Blanco, Liam Smith

CURCE Annual Undergraduate Conference

Studies on educational data mining have massively advanced the analytical understanding of student learning, outcome predictions, student modeling, and better evaluation. While the information retrieved can improve educational outcomes, such studies must not break the wall of trust or compromise student privacy. To this end, it’s imperative to understand the methods of how privacy is ensured in the field of educational data mining and learning analytics, the limitations of these strategies, the complications that may follow, and the possible resolutions. In this project, we take a systematic approach to review studies in the educational data mining field. Initially, we examine …

Automated Segmentation Of Brain Ventricles Using 3d U-Net, Robert Sandor, Anish P. Dalal

Creative Activity and Research Day - CARD

Neuro-radiologists currently use qualitative volumetric change of brain ventricles after surgery to assess the safety of removing a ventriculoperitoneal (VP) shunt which is a medical device that relieves pressure on the brain caused by fluid accumulation. Following safe removal of the VP shunt, patients can be released from the hospital. The need for accurate and quick measurement of brain ventricular volumetric change makes automatic 3D segmentation software an ideal candidate to aid decisions after surgery. In this paper, we propose an approach to estimate the ventricular volume variation using segmentation in brain MRI and CT images. Our approach consists of …