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With the increased presence of image-based data in modern applications, the need for robust methods of image denoising grows greater. The work presented herein considers two of the most ubiquitous approaches towards image denoising: variational and non-local methods. The effectiveness of these methods is assessed using quantitatively using peak signal-to-noise ratio and structural similarity index measure metrics. This study employs ��−means clustering, an unsupervised machine learning algorithm, to isolate the most dominant cluster centroids within the incoming data and propose the introduction of a new adaptive parameter into the non-local means framework. Motivated by the fact that a majority of discrepancies between clean and denoised images occur at feature edges, this study examines several convolution-based edge detection methods to isolate relevant feature. The resultant gradient and edge information is used to further parameterize the ��−means non-local method. An additional hybrid method involving the combined contributions of variational and ��−means non-local denoising is proposed, with the weighting determined by edge intensities. This method outperforms the other methods outlined in the study, both conventional and newly presented.

The main objective of this research was to create a two dimensional and three dimensional Environmental Fluid Dynamics Code (EFDC) model using Aberdeen Pool of the Tennessee-Tombigbee Waterway for the purpose of determining the differences in their ability to address sediment transport. These objectives were reached in the results with comparisons of water levels, sediment concentrations, shear stress, and bed change. The models produced very similar results for the majority of the sediment transport throughout both models with the overall trend being deposition except in the upper limits of the Tombigbee River. The main differences between the two models are produced from the 2D model being depth averaged and the 3D being able to transport sediment vertically. The results show the 2D model tends to erode less and deposit more whereas the 3D model tends to follow the same pattern except for less deposition with more erosion.

In the effort to simulate the biologically inspired continuum robot’s dynamic capabilities, researchers have been faced with the daunting task of simulating—in real-time—the complete three dimensional dynamics of the the “beam-like” structure which includes the three “stiff” degrees-ofreedom transverse and dilational shear. Therefore, researchers have traditionally limited the difficulty of the problem with simplifying assumptions. This study, however, puts forward a solution which makes no simplifying assumptions and trades off only the real-time requirement of the desired solution. The solution is a Finite Difference Time Domain method employing an explicit single step method with cheap right hands sides. The cheap right hand sides are the result of a rather ingenious formulation of the classical beam called the Cosserat rod by, first, the Cosserat brothers and, later, Stuart S. Antman which results in five nonlinear but uncoupled equations that require only multiplication and addition. The method is therefore suitable for hardware implementation thus moving the real-time requirement from a software solution to a hardware solution.

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Abstract Not Provided. / Thesis / Master of Engineering (MEngr)

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