UHD REU Program > Project Description

1. Security-Aware Routing Algorithms

Mentor: Dr. Shengli Yuan

Internet is an extremely complex system with mixtures of diverse technologies and devices. With more and more Internet traffic carrying sensitive data, network security is increasingly causing major concerns. As the core components of the Internet, routers have the important responsibility of directing large amount of traffic dynamically in real time. Any failures or security breaches on Internet routers can cause major interruptions and/or information loss. Despite major improvements, most of the routing algorithms in use today may still be susceptible to various security attacks. Students will study and categorize these routing algorithms and the security attacks, and develop solutions to help the network providers and end-users to better secure their networks. Students will analyze current routing algorithms and identify their weaknesses to various security attacks. Students will design and develop new algorithms that are immune or are less vulnerable to certain attacks. For the algorithms they developed, students need to perform simulations and collect and analyze a large amount of data in order to validate the effectiveness of the algorithms.


2. Parallel Brain Waves Analysis

Mentor: Hong Lin

The objective of this project is to create a program for brain states analysis, in particular, the comparison of meditative states to other brain states. Applications on iPad and Android and a website for information sharing will be included in the project. Mental discipline and meditative practice can change the workings of the brain and allow people to achieve different levels of awareness. The brain is an electrochemical organ using electromagnetic energy to function. Electrical activity emanating from the brain is displayed in the form of brainwaves. The objective of this project is to create a program that is able to analyze these brainwaves when a person is in various states. In particular, we are interested in comparing the brain state of persons in meditative state to brain states of a person during exercise, sleep, study, etc. The program can display the brainwaves in a graph and do a peer-to-peer comparison between different states. Currently, we are collaborating with researchers in the University of Canberra, Australia, in brain waves data collection and analysis.

3. Driver’s Buddy: Designing a real-time facial physiology-based feedback system to improve driver’s performance

Mentor: Dvijesh Shastri

Many attempts were made in the past to monitor a driver’s visual and cognitive distractions. Yet, most of the techniques did not become a practical application due to their contact-based nature of monitoring. Among others, biomarkers and physiology sensors were proposed for the monitoring . The disadvantage of these technologies is that they require close contact with the driver, which not only offers an uncomfortable driving environment but also introduces significant amount of motion error in the measurements. In our previous study, we demonstrated the correlation of increased blood perfusion in the supraorbital muscles and machine operator’s mental overloading [4]. The proposed work aims at extending this research by developing a real-time feedback system to alert the operator about his/her psychological status based on the facial thermal signature.
A driving simulator will be used as a test bed in the indoor laboratory setup. Primary efforts will be focused on the development of software modules and hardware components. The software modules will analyze the facial thermal signature in real-time and send digital triggers to the hardware components. Depending on the trigger types, the hardware components will alter the vehicle’s ambience in order to achieve a desired psychological state of the driver. Take for example drowsiness while driving that is a leading cause of major accidents. The proposed feedback system will detect the driver’s psychological state from his/her facial physiology and alert the driver by providing audio cues or by changing music in the vehicle.
Undergraduate Involvement: The student will assist in designing the experiment and implementing the software modules and hardware components. In particular, they will be involved in analysis of the thermal signals via various pattern classification algorithms. The students will also be interacting with doctoral candidates at the University of Houston-Central campus which will be pivotal in their pursuit for the higher education.


UHD REU site is sponsored by National Science Foundation and Scholar Academy.

University of Houston-Downtown
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