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Aortic valve dynamics - which implies continuous opening and closing of the aortic valve in each cardiac cycle during the feedback control of the rotary Left Ventricular Assist Devices (LVAD) support - has important clinical implications for patients with mild congestive heart failure. When the LVAD is implanted in such patients as a bridge-to-recovery device, permanent closure of the aortic valve...
The left ventricular assist device is a rotary mechanical pump that is implanted in patients with congestive heart failure to help the left ventricle in pumping blood in the circulatory system. However, using such a device may result in a very dangerous event, called ventricular suction, that can cause ventricular collapse due to overpumping of blood from the left ventricle when the rotational speed...
A new suction detection algorithm for rotary Left Ventricular Assist Devices (LVAD) is presented. The algorithm is based on a Lagrangian Support Vector Machine (LSVM) model. Six suction indices are derived from the LVAD pump flow signal and form the inputs to the LSVM classifier. The LSVM classifier is trained and tested to classify pump flow patterns into three states: No Suction, Approaching Suction,...
In tennis match highlights mainly take place in shots containing full court (Court view shots), therefore successful court view shots detection is useful for highlights extraction. This paper proposes a court view shots detection algorithm, in which shot detection that is the precondition of usual shot classification is given up for shot detection not only costs more time, but also its detection performance...
The LAMOST (large sky area multi-object fiber spectroscopic telescope) is one of the national key scientific projects. It will yield 10,000~20,000 spectra per observation night. Automatic spectral analysis and recognition focused on helping astronomers finding their interesting celestial objects. become desirable and necessary. In this paper an efficient data mining application based on improved Principal...
Pattern recognition may be used for crack size and type classification in ultrasonic nondestructive evaluation. Feature selection and reduction of computational complexity are two important problems to be solved in the development of pattern recognition algorithms. This paper describes a classifier based on support vector machines (SVM) and principal component analysis (PCA). The proposed approach...
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