Everything exists and evolves within time–space and time–space is within everything, from a
molecule to the universe. Understanding the complex relationship between time and space …

Neural network (NN) finds role in variety of applications due to combined effect of feature
extraction and classification availability in deep learning algorithms. In this paper, we have …

Deep learning has achieved excellent performance in a wide range of domains, especially
in speech recognition and computer vision. Relatively less work has been done for …

An active machine learning technique for monitoring the voltage stability in transmission
systems is presented. It has been shown that machine learning algorithms may be used to …

Mental stress is an increasingly common psychological issue leading to diseases such as
depression, addiction, and heart attack. In this study, an early detection framework based on …

Electrocardiogram (ECG) heartbeat classification plays a vital role in early diagnosis and
effective treatment, which provide opportunities for earlier prevention and intervention. In an …

This paper introduces a new methodology for dynamic learning, visualization, and
classification of functional magnetic resonance imaging (fMRI) as spatiotemporal brain data …

Recent technological advances in machine learning offer the possibility of decoding
complex datasets and discern latent patterns. In this study, we adopt Liquid State Machines …

There has been substantial interest in Mindfulness Training (MT) to understand how it can
benefit healthy individuals as well as people with a broad range of health conditions …

The high incidence of stroke occurrence necessitates the understanding of its causes and
possible ways for early prediction and prevention. In this respect, statistical methods offer the …