Physical Sciences and Mathematics Commons^™

P300-Based Bci Performance Prediction Through Examination Of Paradigm Manipulations And Principal Components Analysis., Nicholas Edward Schwartz

Electronic Theses and Dissertations

Severe neuromuscular disorders can produce locked-in syndrome (LIS), a loss of nearly all voluntary muscle control. A brain-computer interface (BCI) using the P300 event-related potential provides communication that does not depend on neuromuscular activity and can be useful for those with LIS. Currently, there is no way of determining the effectiveness of P300-based BCIs without testing a person's performance multiple times. Additionally, P300 responses in BCI tasks may not resemble the typical P300 response. I sought to clarify the relationship between the P300 response and BCI task parameters and examine the possibility of a predictive relationship between traditional oddball tasks …

A Study Of Improving The Parallel Performance Of Vasp., Matthew Brandon Baker

Electronic Theses and Dissertations

This thesis involves a case study in the use of parallelism to improve the performance of an application for computational research on molecules. The application, VASP, was migrated from a machine with 4 nodes and 16 single-threaded processors to a machine with 60 nodes and 120 dual-threaded processors. When initially migrated, VASP's performance deteriorated after about 17 processing elements (PEs), due to network contention. Subsequent modifications that restrict communication amongst VASP processes, together with additional support for threading, allowed VASP to scale up to 112 PEs, the maximum number that was tested. Other performance-enhancing optimizations that were attempted included replacing …

Early Stopping Of A Neural Network Via The Receiver Operating Curve., Daoping Yu

Electronic Theses and Dissertations

This thesis presents the area under the ROC (Receiver Operating Characteristics) curve, or abbreviated AUC, as an alternate measure for evaluating the predictive performance of ANNs (Artificial Neural Networks) classifiers. Conventionally, neural networks are trained to have total error converge to zero which may give rise to over-fitting problems. To ensure that they do not over fit the training data and then fail to generalize well in new data, it appears effective to stop training as early as possible once getting AUC sufficiently large via integrating ROC/AUC analysis into the training process. In order to reduce learning costs involving the …

Generating Compact Wasp Nest Structures Via Minimal Complexity Algorithms., Fadel Ewusi Kofi Adoe

Electronic Theses and Dissertations

Many models have been developed to explain the process of self organization-the emergence of seemingly purposeful behaviors from groups of entities with limited individual intelligence. However, the underlying behavior that facilitates the emergence of this global pattern is not generally well understood. Our study focuses on different low complexity building algorithms and characterizes how nests are built using these algorithms. Three rules postulated to be functions of wasps' building behavior were developed. First is the random rule, in which there is no constraint per the choice of site to be initiated. The second is the 2-cell rule where only sites …

Using Ant Colonization Optimization To Control Difficulty In Video Game Ai., Joshua Courtney

Undergraduate Honors Theses

Ant colony optimization (ACO) is an algorithm which simulates ant foraging behavior. When ants search for food they leave pheromone trails to tell other ants which paths to take to find food. ACO has been adapted to many different problems in computer science: mainly variations on shortest path algorithms for graphs and networks.

ACO can be adapted to work as a form of communication between separate agents in a video game AI. By controlling the effectiveness of this communication, the difficulty of the game should be able to be controlled. Experimentation has shown that ACO works effectively as a form …