Human biomechanics and gait form an integral part of life. The gait analysis involves a large
number of interdependent parameters that were difficult to interpret due to a vast amount of …

Background automatic recognition of human movement is an effective strategy to assess
abnormal gait patterns. Machine learning approaches are mainly applied due to their ability …

Fault detection in photovoltaic (PV) arrays becomes difficult as the number of PV panels
increases. Particularly, under low irradiance conditions with an active maximum power point …

Machine learning methods have been widely used for gait assessment through the
estimation of spatio-temporal parameters. As a further step, the objective of this work is to …

Protection devices are extensively utilized in direct current (DC) systems to ensure their
normal operation and safety. However, series arc faults that establish current paths in the air …

The increasing amount of data in biomechanics research has greatly increased the
importance of developing advanced multivariate analysis and machine learning techniques …

In literature, features based on First and Second Order Statistics that characterizes textures
are used for classification of images. Features based on statistics of texture provide far less …

Obstructive sleep apnea syndrome (OSAS) is associated with cardiovascular morbidity as
well as excessive daytime sleepiness and poor quality of life. In this study, we apply a …

In this study, heartbeat time series are classified using support vector machines (SVMs).
Statistical methods and signal analysis techniques are used to extract features from the …

This paper describes a large-scale gait database comprising the Treadmill Dataset. The
dataset focuses on variations in walking conditions and includes 200 subjects with 25 views …