History of Computing
A single page React website that compares and contrasts the historical timelines in both the history of computing and the history of culture.
The Metrics Dashboard is research software to apply classical in-process and code metrics to observe team progress and project health in open source projects.
Testing Effectiveness is an effort to explore existing and new metrics specific to software testing over time. As a codebase grows, we hope that its testing code would also grow. We’re also interested in how existing metrics (coverage) correlate with classic metrics, such as defect density.
The goal of Voltkey is to make the deployment and maintenance of new IoT devices easy. Currently, when we install new IoT devices, we need to go through a complex process of connecting the device to the WiFi network. With Voltkey, no configuration is necessary: you just plug the new device in and it works.
FLIC: Fog Linked Internet of Things Cache
FLIC: Fog Linked Internet of Things Cache is a fog computing project which makes a fog topology more efficient with its bytes in and bytes out.
Hermes is a hypervisor for MCU-based systems with real-time requirements. The goal of Hermes is to manage tradeoffs between performance and flexibility in software that runs on embedded systems.
Laptop Ensemble and Software
The Loyola University Technology Ensemble performs using a collection of tools for interactive music performance. These tools allow for a group performance on laptops and to allow for tracking of progress through a group-performed composition.
Non-Local Mean Curvature
Non-Local Mean Curvature is a mathematics project centered around writing algorithms for analytical mathematical concepts in a parallel way.
The Shape Analysis project is a collaboration between Loyola University Chicago, Louisiana State University, and the University of Connecticut that explores the performance of machine learning algorithms on the classification of fossil teeth in the Family Bovidae. Isolated bovid teeth are typically the most common fossils found in southern Africa and they often constitute the basis for paleoenvironmental reconstructions. Taxonomic identification of fossil bovid teeth, however, is often imprecise and subjective. Using modern teeth with known taxons, machine learning algorithms can be trained to classify fossils.