Recently, the COVID-19 epidemic has resulted in millions of deaths and has impacted
practically every area of human life. Several machine learning (ML) approaches are …

Neuromorphic computing has been attracting ever‐increasing attention due to superior
energy efficiency, with great promise to promote the next wave of artificial general …

Spiking neural networks (SNNs) are regarded as a promising candidate to deal with the
major challenges of current machine learning techniques, including the high energy …

Combined cycle power plants (CCPP) are among the most sophisticated, yet efficient,
systems for producing electrical energy. Hence, simulating their performance has been an …

Working memory is a fundamental feature of biological brains for perception, cognition, and
learning. In addition, learning with working memory, which has been show in conventional …

To investigate the diversified technologies in Internet of Vehicles (IoVs) under intelligent
edge computing, brain-inspired computing techniques are proposed in this study, which is a …

Human activity recognition (HAR) is an important task in many applications such as smart
homes, sports analysis, healthcare services, etc. Popular modalities for human activity …

Abstract Sine Cosine Algorithm (SCA), as a recently viral population-based meta-heuristic,
which is in the extensive application for a variety of optimization cases. Regardless of the …

Due to the challenging constraint search space of real-world engineering problems, a
variation of the Chimp Optimization Algorithm (ChOA) called the Universal Learning Chimp …

Accurate emotion recognition can drive the robot to understand human affection intentions
precisely and deliver the emotional response when communicating with a person. Recently …