-
Culture Conditions Influence Iridescence in Marine Microbes
Author: J Livingston Mentor: Dr. George O’Toole, Dr. Dianne Newman, Co-Mentor: Lynn Kee Editor: Grace Xiong Introduction Microbiology is the study of microorganisms: how they grow, where they are found, and how they interact with each other and their environment.1,2 The study of microbiology allows researchers to develop a better understanding of the basic processes…
-
2017 Issue
curj_su2017_cover
-
Convolutional Neural Networks as Efficient Emulators for Atmospheric Models
Author: Berlin Chen Mentors: Hai Nguyen, Derek Posselt Editor: Michael Yao Abstract We used Convolutional Neural Networks (CNNs) to emulate the physics of the atmosphere in order to bypass solving partial-differential equations (PDEs) explicitly, which cuts down on computational cost. This is important because in the past, the models used to produce reliable weather forecasts…
-
Detection of Volume Changes in Greenland’s Marine Terminating Glaciers
Increased melting of marine-terminating glaciers of the Greenland Ice Sheet could lead to unstable dynamic ice mass loss, further accelerating global sea level rise. To better understand the historical context of the present-day widespread glacier front retreat, we mapped frontal positions for two years, 1994 and 2017, for 146 and 251 major outlet glaciers, respectively.…
-
Machine Learning for Cybersecurity: Network-based Botnet Detection Using Time-Limited Flows
Author: Stephanie Ding Mentor: Julian Bunn Editor: Sherry Wang Abstract Botnets are collections of connected, malware-infected hosts that can be controlled by a remote attacker. They are one of the most prominent threats in cybersecurity, as they can be used for a wide variety of purposes including denial-of-service attacks, spam or bitcoin mining. We propose…