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Deep learning algorithms produces state-of-the-art results for different machine learning and computer vision tasks. To perform well on a given task, these algorithms require large dataset for training. However, deep learning algorithms lack generalization and suffer from over-fitting whenever trained on small dataset, especially when one is dealing with medical images. For supervised image analysis...
For most large-scale systems, centrality is simply not feasible because it requires expensive and sophisticated data acquisition and communication networks. Moreover, with the integration of large-scale distributed energy resources into the power systems, it is desired to divide a one large system into multiple small systems to make the analysis and control feasible and comparatively easier. In this...
The problem of regulating voltages within the required limits is complicated by the fact that power system supplies power to a vast number of loads and is fed from many generating units. As loads vary, reactive power requirements of the transmission system vary. Moreover, voltage magnitude is relatively less sensitive to active power compared to reactive power due to high X/R ratio of transmission...
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