The advent of the sixth generation of mobile communications (6G) ushers in an era of
heightened demand for advanced network intelligence to tackle the challenges of an …

Utilizing data acquired by multiple wearable sensors can usually guarantee more accurate
recognition for deep learning based human activity recognition. However, an increased …

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 …

Recent trends in Wearable Human Activity Recognition (WHAR) have led to an
unprecedented 42.9% increase in scholarly articles in 2022, underscoring the urgency for a …

Smartphones and wearable devices have built-in sensors that can collect multivariant time-
series data that can be used to recognize human activities. Research on human activity …

Location indices are key in explaining variation in house prices. However, the definition of
comprehensive indices capturing all locational features, along with their efficient and timely …

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 …

Extracting representative features to recognize human activities through the use of
wearables is an area of on-going research. While hand-crafted features and machine …

Abstract Human Activity Recognition (HAR) is the process of automatic recognition of
Activities of Daily Living (ADL) from human motion data captured in various data modalities …