PhD Theses

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PhD Theses

Blast-induced traumatic brain injury (b-TBI) is regarded as the ‘signature injury’ of modern violent conflict. It has been repeatedly linked to numerous neuropathologies, which are common among military personnel and Veterans. 

Data visualization provides a human-digestible interface to digital data. With increasing data volumes and increased complexity and interrelationships, so have the demands on supporting effective visualization to support this interface. With complex data at scale, it becomes necessary to summarize the data in some manner to communicate high-level information of a dataset, such as distributions, trends, or anomalies. 

River bridge scour is an erosion process in which flowing water removes sediment materials (such as sand, rocks) from a bridge foundation, river beds and banks. As a result, the level of the river bed near a bridge pier is lowering such that the bridge foundation stability can be compromised, and the bridge can collapse.

Perreault, Logan Jared. (Montana State University) “On the Usability of Continuous Time Bayesian Networks: Improving Scalability and Expressiveness” (2017), Advisor: Sheppard, John W., https://www.cs.montana.edu/sheppard/

Igor Moáco Guerreiro, Federal University of Ceará, Brazil (2017), "Distributed optimization techniques for 4G and beyond", advisor: Charles Casimiro Cavalcante

Pourkamali Anaraki, Farhad. University of Colorado at Boulder,(2017) "Randomized Algorithms for Large-Scale Data Analysis", advisor: Becker, Stephen

Massive high-dimensional data sets are ubiquitous in all scientific disciplines.

Fan, Bin. Michigan State University, (2017) "Polycrystalline diamond based neural interface for optogenetics and neurotransmitter detection" advisor: Wen Li

Zhu, Zhenghan. University of Rhode Island (2017)"Some Contributions to Radar Detection Theory", advisor: Kay, Steven

Kaewtip, Kantapon. University of California, Los Angeles(2017)"Robust Automatic Recognition of Birdsongs and Human Speech: a Template-Based Approach", advisor: Alwan, Abeer

Hossein Bashashati, University of British Columbia (2017) "A User-Customized Self-Paced Brain Computer Interface", advisor: Gary Birch

Much attention has been directed towards synchronous Brain Computer Interfaces (BCIs). For these BCIs, the user can only operate the system during specific system-defined periods. Self-paced BCIs, however, allow users to operate the system at any time he/she wishes. The classification of Electroencephalography (EEG) signals in self-paced BCIs is extremely challenging.

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