Arts and Humanities Commons^™

Knowledge-Guided Processing Of Magnetic Resonance Images Of The Brain, Matthew C. Clark

USF Tampa Graduate Theses and Dissertations

This dissertation presents a knowledge-guided expert system that is capable of applying routinesfor multispectral analysis, (un)supervised clustering, and basic image processing to automatically detect and segment brain tissue abnormalities, and then label glioblastoma-multiforme brain tumors in magnetic resonance volumes of the human brain. The magnetic resonance images used here consist of three feature images (T1-weighted, proton density, T2-weighted) and the system is designed to be independent of a particular scanning protocol. Separate, but contiguous 2D slices in the transaxial plane form a brain volume. This allows complete tumor volumes to be measured and if repeat scans are taken over time, …

The Political Legacy Of School Accountability Systems, Sherman Dorn

Educational and Psychological Studies Faculty Publications

The recent battle reported from Washington about proposed national testing program does not tell the most important political story about high stakes tests. Politically popular school accountability systems in many states already revolve around statistical results of testing with high-stakes environments. The future of high stakes tests thus does not depend on what happens on Capitol Hill. Rather, the existence of tests depends largely on the political culture of published test results. Most critics of high-stakes testing do not talk about that culture, however. They typically focus on the practice legacy of testing, the ways in which testing creates perverse …

Dios Entre Arreola Y La Literatura Fantastica, Pablo A.J. Brescia

World Languages Faculty Publications

No abstract provided.

An Application Of Artificial Neural Networks In Freeway Incident Detection, Sujeeva A. Weerasuriya

USF Tampa Graduate Theses and Dissertations

Non-recurring congestion caused by incidents is a major source of traffic delay in freeway systems. With the objective of reducing these traffic delays, traffic operation managers are focusing on detecting incident conditions and dispatching emergency management teams to the scene quickly. During the past few decades, a few number of conventional algorithms and artificial neural network models were proposed to automate the process of detecting incident conditions on freeways. These algorithms and models, known as automatic incident detection methods (AIDM), have experienced a varying degree of detection capability.

Of these AIDMs, artificial neural network-based approaches have illustrated better detection performance …