Human-machine interfaces have penetrated various academia and industry fields such as smartphones, robotic, virtual reality, and wearable electronics, due to their abundant functional sensors and information interaction methods. Nevertheless, most se...
Multivariate time series forecasting has long been a research hotspot because of its wide range of application scenarios. However, the dynamics and multiple patterns of spatiotemporal dependencies make this problem challenging. Most existing methods ...
The increasing energy demand and the target to reduce environmental pollution make it essential to use efficient and environment-friendly renewable energy systems. One of these systems is the Photovoltaic (PV) system which generates energy subject to...
This study proposed a medicine auxiliary diagnosis model based on neural network. The model combines a bidirectional long short-term memory(Bi-LSTM)network and bidirectional encoder representations from transformers (BERT), which can well complete th...
The journal of physical chemistry letters
Dec 23, 2021
Inspired by the brain, future computation depends on creating a neuromorphic device that is energy-efficient for information processing and capable of sensing and learning. The current computation-chip platform is not capable of self-power and neurom...
The development of artificial intelligence and the Internet of things has motivated extensive research on self-powered flexible sensors. The conventional sensor must be powered by a battery device, while innovative self-powered sensors can provide po...
This paper presents an artificial neural network-based adaptive control approach for a doubly-fed induction generator (DFIG) based wind energy conversion system (WECS). The control objectives are: (1) extraction of maximum available power from the wi...
BACKGROUND: Early and accurate radiographic diagnosis is required for the management of children with radio-opaque esophageal foreign bodies. Button batteries are some of the most dangerous esophageal foreign bodies and coins are among the most commo...
This paper presents a neural-network based nonlinear behavioral modelling of I/O buffer that accounts for timing distortion introduced by nonlinear switching behavior of the predriver electrical circuit under power and ground supply voltage (PGSV) va...
In power system networks, automatic fault diagnosis techniques of switchgears with high accuracy and less time consuming are important. In this work, classification of abnormal location in switchgears is proposed using hybrid gravitational search alg...
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