Electromyography (EMG) signal is a measure of muscles' electrical activity and usually
represented as a function of time, defined in terms of amplitude, frequency and phase. This …

The emergence of cloud environments has made feasible the delivery of Internet-scale
services by addressing a number of challenges such as live migration, fault tolerance and …

Today's advanced muscular sensing and processing technologies have made the
acquisition of electromyography (EMG) signal which is valuable. EMG signal is the …

This paper presents the design, optimization and performance evaluation of artificial neural
network for the efficient classification of Electromyography (EMG) signals. The EMG signals …

Most myoelectric controlled systems are based on the common assumption that there is no
information in the instantaneous value of the myoelectric signal and therefore, analysis is …

Hand and arm gestures are a great way of communication when you don't want to be heard,
quieter and often more reliable than whispering into a radio mike. In recent years hand …

This paper presents a new design of mobile epilepsy warning system for medical application
in telemedical environment. Mobile Epilepsy Warning System (MEWS) consists of a wig with …

The goal of proposed study is to specify Second Language Learning (SLL) and affective
factors among variables of five language skills analyzed by using different Deep Neural …

Neural networks are increasingly being used in real-world business applications and, in
some cases, such as fraud detection, they have already become the method of choice. Their …

This paper describes results concerning the classification capabilities of supervised
machine learning methods in detecting intrusions using network audit trails. In this paper we …