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Articles 1 - 3 of 3
Full-Text Articles in Engineering
Intra-Hour Solar Forecasting Using Cloud Dynamics Features Extracted From Ground-Based Infrared Sky Images, Guillermo Terrén-Serrano
Intra-Hour Solar Forecasting Using Cloud Dynamics Features Extracted From Ground-Based Infrared Sky Images, Guillermo Terrén-Serrano
Electrical and Computer Engineering ETDs
Due to the increasing use of photovoltaic systems, power grids are vulnerable to the projection of shadows from moving clouds. An intra-hour solar forecast provides power grids with the capability of automatically controlling the dispatch of energy, reducing the additional cost for a guaranteed, reliable supply of energy (i.e., energy storage). This dissertation introduces a novel sky imager consisting of a long-wave radiometric infrared camera and a visible light camera with a fisheye lens. The imager is mounted on a solar tracker to maintain the Sun in the center of the images throughout the day, reducing the scattering effect produced …
Unsupervised Data Driven Machine Learning In Hyperspectral Imaging And Echocardiography Videos, Kazi Tanzeem Shahid
Unsupervised Data Driven Machine Learning In Hyperspectral Imaging And Echocardiography Videos, Kazi Tanzeem Shahid
Electrical Engineering Dissertations
This work discusses the problem of unsupervised classification in images. Conventional methods approached this problem with the naive assumption that the relationship among the pixels' information can be expressed sufficiently in a linear manner. However, higher accuracy was established by implementing kernel-based expressions of data to express the non-linear relationship of that data in a linear manner, when mapped in a higher dimensional space. This process allows much more effective clustering performances by increasing the informativeness of the data. Hyperspectral images, being limited in spatial resolution as a tradeoff for the significantly higher number of channels compared to traditional images, …
Kernels And Beyond For Data Similarity Learning In Data Mining, Akshay Malhotra
Kernels And Beyond For Data Similarity Learning In Data Mining, Akshay Malhotra
Electrical Engineering Dissertations
This work discusses the problem of unsupervised clustering of signals/data vectors based on their information content. A correlation based perspective to the clustering problem has been considered, thus relying on the high correlation between data vectors from the same class rather than on the position of the vectors in the data space. In the past, correlation based clustering has been formulated using a canonical correlation framework or as a matrix factorization problem and has been solved with different variants of gradient descent. This work focuses on improving the clustering performance by modifying the framework to utilize non-linear associations or correlations. …