You are here
2015 Evans Student Research Fellowship Program
Through a generous donation from ONU alumnus, Tom Evans, BSCE ’45, the College of Engineering has established the Evans Student Research Fellowship program, which will provide students in the college the opportunity to work with faculty over the summer on undergraduate research projects. This program will provide funding for 10 weeks of work during the summer at the ONU research rate of $13.36 per hour. Two students will be selected as Evans Fellows to work with faculty on one of two research projects. The two projects are listed below. Please complete the webform at the bottom of this page to apply to become an Evans Fellow.
All applications are due to be submitted by Friday, April 10
Resilient Vehicle-to-Vehicle Communication Protocols
Dr. Nesreen Alsbou, Dr. Heath LeBlanc and Dr. Firas Hassan
Vehicle-to-Vehicle communication (V2V) is a new technology which will help drivers become safer and more aware of their surroundings. It will prevent traffic jams and collisions through communication with other vehicles on the road and enable autonomous vehicles to be integrated with human-driven vehicles on the highway. Vehicle communication systems can be implemented in vehicles and on the roadsides, which will allow the vehicles to transmit and receive messages from one another using a communication protocol. The protocol used must be reliable, secure, and resilient and be able to distinguish between the data being communicated and the senders/sources of the data. The data can be of high or low priority and from trusted or untrusted sources. In this project, we will analyze V2V network efficiency and reliability using a MAC protocol called PR-ALOHA which deals with two types of data: high priority and low priority data. We will add security and resilience to the PR-ALOHA protocol and then determine the performance in the case where some of the vehicles are malicious. Such malicious vehicles behave as adversaries and aim to cause traffic jams or collisions by providing false data. In addition to this, various mobility models will be studied to see how the PR-ALOHA performs in V2V networks under different mobility models both with and without additional security measures in place.
Real-Time Adaptations to Changes in Ankle Stiffness During Gait
Dr. Louis DiBerardino
Walking is a fundamental task most people rely on throughout their daily routine. Patients suffering from many different injuries or pathologies strive to maintain their walking ability by developing compensatory strategies. While there is great interest in how patients compensate for particular injuries, much of the focus is specifically placed on the healing process in order to refine rehabilitation methods and track recovery. For example, certain populations have shown better adoption of successful compensation strategies than others during functional tasks after anterior cruciate ligament repair. These results suggest a need to more fully understand the compensation strategies developed by the neuromuscular control system (NCS) throughout recovery from injury. Previously, I have performed an experiment analyzing the manner in which steady-state compensations during gait (after sufficient adaptation time) change while recovering from an injury. The injury was simulated as increased ankle stiffness from an orthotic device. Recovery was simulated by a systematic reduction along discrete stiffness levels. For the current project, existing (unused) data from the aforementioned experiment will be analyzed to study the real-time adaptations caused by change in ankle stiffness. In other words, focus will be placed on how subjects' compensations change immediately after a change in ankle stiffness. Results from this work will allow us to assess NCS ability and effectiveness at overcoming changes in joint stiffness, and extend the understanding of how certain injury compensation strategies are arrived at. Work will involve processing raw experimental data, calculating kinematics and kinetics of the lower limbs via MATLAB, and analyzing adaptation patterns of these data for presentation.