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We propose a methodology to predict the cardiac epicardial and mediastinal fat volumes in computed tomography images using regression algorithms. The obtained results indicate that it is feasible to predict these fats with a high degree of correlation, thus alleviating the requirement for manual or automatic segmentation of both fat volumes. Instead, segmenting just one of them suffices, while the...
The work presents measurements of harmonics and interharmonics from a modern wind turbine over a period of several days, using a conventional power quality monitor. A statistical study has been performed to present the characteristics of the emission during the measurement. A variation of emission has been observed, especially for interharmonics within certain low-frequency bands and for the switching...
The problem of outlier detection is well studied in the fields of Machine Learning (ML) and Knowledge Discovery in Databases (KDD). Both fields have their own methods and evaluation procedures. In ML, Support Vector Machines and Parzen Windows are well-known methods that can be used for outlier detection. In KDD, the heuristic local-density estimation methods LOF and LOCI are generally considered...
Upper limb weakness due to Multiple Sclerosis has a major negative effect on the functional activities of the patient. Promising developments in the field of rehabilitation robotics may enable additional exercise. This study aims to investigate which types of robotic outcome measures are clinically relevant, in preparation of the evaluation for intervention studies.Within this context, appropriate...
This paper proposes an efficient and reliable blind channel estimation method for single transmitter and receiver antenna orthogonal frequency division multiplexing (OFDM) system. The proposed blind channel estimation method is based on the interesting cross-correlation property of the repeated structure of cyclic prefix (CP) in an OFDM symbol. Our cross-correlation based method, which utilizes the...
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