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This work presents our effort in analyzing human bio signals collected during sleep studies, to automatically detect events related to sleep disorders. We experiment with real sleep data collected using standard Polysomnography (PSG), and we detect events of interest from EEG signals, by segmenting the signal, extracting descriptive features from each segment, and applying supervised learning for...
Forest fire early detection is an important problem from many points of view. It harms ecology and decreases the overall life quality also it is important from economical point of view as wood is a valuable recourse. In this paper, we examine the problem of early fire/smoke detection using shots of different parts of the controlled forest terrain. Our approach is based on image full segmentation,...
A comprehensive harmonic monitoring program has been designed and implemented on a typical medium-voltage distribution system in Australia. The monitoring program involved measurements of the three-phase harmonic currents and voltages from the residential, commercial, and industrial load sectors. Data over a three year period have been downloaded and available for analysis. The large amount of acquired...
Kidney cancer occurs in both hereditary (inherited) and sporadic (non-inherited) form. It is estimated that almost a quarter of a million people in the USA are living with kidney cancer and their number increases, with 51,000 diagnosed with the disease every year. In clinical practice, the response to treatment is monitored by manual measurements of tumor size, which are 2D, do not reflect the 3D...
Harmonic monitoring has become an important tool for harmonic management in distribution system. A comprehensive harmonic monitoring program has been designed and implemented on a typical electrical medium-voltage distribution system in Australia. The monitoring program involved measurements of the three-phase harmonic currents and voltages from the residential, commercial, and industrial load sectors...
In many of clustering algorithms, such as K-means and Fuzzy C-mean, the value of the expected numbers of clusters is often needed in advance as an input parameter to the algorithm. Other clustering algorithms estimate this number as the clustering process progresses using various heuristic techniques; however such techniques can also lead to a local minima within the solution space without finding...
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