Physical Sciences and Mathematics Commons^™

Design And Implementation Of A Multi-Port Solid State Transformer For Flexible Der Integration, Mohammad Rashidi

Theses and Dissertations

Conventional power system includes four major sections, bulk generation, transmission network, distribution network, and loads. The main converter in the conventional electric grid is the low-frequency passive transformer providing galvanic isolation and voltage regulation for various voltage zones. In this configuration, small-scale renewable energy resources are generally connected to the power system at low voltage zones or inside microgrids.

Recent developments in the design of power electronic elements with higher voltage and power ratings and medium/high frequency enable making use of solid state transformer at different voltage levels in the distribution system and microgrid design. In this work, the concept …

Threshold Free Detection Of Elliptical Landmarks Using Machine Learning, Lifan Zhang

Theses and Dissertations

Elliptical shape detection is widely used in practical applications. Nearly all classical ellipse detection algorithms require some form of threshold, which can be a major cause of detection failure, especially in the challenging case of Moire Phase Tracking (MPT) target images. To meet the challenge, a threshold free detection algorithm for elliptical landmarks is proposed in this thesis. The proposed Aligned Gradient and Unaligned Gradient (AGUG) algorithm is a Support Vector Machine (SVM)-based classification algorithm, original features are extracted from the gradient information corresponding to the sampled pixels. with proper selection of features, the proposed algorithm has a high accuracy …

Bayesian Methods And Machine Learning For Processing Text And Image Data, Yingying Gu

Theses and Dissertations

Classification/clustering is an important class of unstructured data processing problems. The classification (supervised, semi-supervised and unsupervised) aims to discover the clusters and group the similar data into categories for information organization and knowledge discovery. My work focuses on using the Bayesian methods and machine learning techniques to classify the free-text and image data, and address how to overcome the limitations of the traditional methods. The Bayesian approach provides a way to allow using more variations(numerical or categorical), and estimate the probabilities instead of explicit rules, which will benefit in the ambiguous cases. The MAP(maximum a posterior) estimation is used to …