Mobile and wearable devices have enabled numerous applications, including activity
tracking, wellness monitoring, and human–computer interaction, that measure and improve …

Human Activity Recognition (HAR) is a field that infers human activities from raw time-series
signals acquired through embedded sensors of smartphones and wearable devices. It has …

Abstract Human Activity Recognition (HAR) involves the recognition of human activities
using sensor data. Most of the techniques for HAR involve hand-crafted features and hence …

Biomedical images contain a huge number of sensor measurements that can provide
disease characteristics. Computer-assisted analysis of such parameters aids in the early …

In the paper, we present a new dual attention method called DanHAR, which blends
channel and temporal attention on residual networks to improve feature representation …

Deep learning (DL)-based intelligent fault diagnosis methods have greatly promoted the
development of the field of fault diagnosis due to their powerful feature extraction ability for …

This paper proposes a new method for encryption of RGB color images by combining two
encryption approaches: the spatial approach and the transformation approach. The …

During the past decade, human activity recognition (HAR) using wearable sensors has
become a new research hot spot due to its extensive use in various application domains …

The rapid advances in the Internet of Things (IoT) have promoted a revolution in
communication technology and offered various customer services. Artificial intelligence (AI) …

There are huge differences in the layouts and numbers of sensors in different smart home
environments. Daily activities performed by residents trigger a variety of sensor event …