In-memory computing (IMC) on a reconfigurable architecture is the emerging field that performs an application-based resource allocation for computational efficiency and energy optimization. In this work, we propose a ...

The distribution system is digitizing and occupying cyberspace with the help of information and communication technologies (ICTs). It is vulnerable to cyber-attacks like false data injection (FDI) and denial-of-services ...

With the proliferation of information and communication technology (ICT), the smart grid is critically vulnerable to cyber-attacks such as false data injection (FDI), denial-of-service, and data spoofing. The cyber-attackers ...

Ultrafast ultrasound localization microscopy (ULM), which has shown promising results in microvascular imaging, overcomes the typical trade-off between resolution and penetration depth. Combining ultrasound contrast agents ...

This paper presents a comparative study of optimal reconfiguration, distributed generation, and shunt capacitor bank deployment for power loss minimization and voltage profile improvement in distribution systems. A ...

Recent studies have shown that virtual gamified therapy can be a potential adjunct to conventional orthopedic rehabilitation. However, the off-the-shelf gaming consoles used for virtual rehabilitation pose several practical ...

The intermittency of renewable energy sources (RES) and dynamic variation of loads may pose threat to the long-term operation of a stand-alone microgrid with critical loads. A local inverter control can only restore the ...

Lithium-ion (Li-ion) batteries are the preferred choice for energy storage applications. Li-ion performances degrade with time and usage, leading to a decreased total charge capacity and to an increased internal resistance. ...

n this paper, a robust Internet-of-Thing (IoT) enabled Smart Energy Management Device (SEMD) is developed for Distributed Energy Resources (DERs) equipped energy consumers. The SEMD communicates with the existing metering ...

Compact and energy-efficient synapse and neurons are essential to realize the full potential of neuromorphic computing. In addition, a low variability is indeed needed for neurons in deep neural networks for higher accuracy. ...