This project utilizes network analysis and agent-based modeling to examine long-standing questions that can only now be asked with the rich data provided in southwestern Colorado and southern France: how Gauls and colonists ...

We describe how the analytic field propagation (AFP) technique can be coupled with a total-field/scattered-field (TFSF) boundary to obtain a novel implementation of a "gen-eralized" total-field/scattered-field (G-TFSF) ...

Generating application-level content within network simulations and/or testbed environments tends toward an ad-hoc process reliant primarily on evaluator expertise. Such ad-hoc approaches are laborious and often fail to ...

Wireless sensor network, composed of tens or hundreds of low-power and resource-constrained devices, has the potential to greatly enhance the understanding of volcanoes by permitting distributed deployments of sensor nodes ...

Smart home technologies and the concept of home automation have become more popular in recent years. This popularity has been accompanied by social acceptance of passive sensors installed throughout the home. The subsequent ...

Packet classification (PC) is the core mechanism used by network devices such as edgerouters, firewalls, and intrusion detection systems to classify incoming traffic based on the classificationpolicy. In decision-tree-based ...

With the ever-increasing abundance of sensing and computing devices embedded into our environments we have the opportunity to create personalized activity recognition ecosystems. Two key challenges must first be overcome, ...

The world is becoming increasingly computerized; much of this computing hardware is put into silicon overseas, increasing the number of unknown or untrusted sourced ICs in critical systems. Current methods of determining ...

The 2012 report by the US President’s Council of Advisors on Science and Technology (PCAST) predicts a deficit in the workforce for science, technology, engineering, and mathematics (STEM) in the following decade and ...

Transfer learning is a method in machine learning that tries to use previous training knowledge to speed up the learning process. Policy advice is a type of transfer learning method where a student agent is able to learn ...