Resistive random access memory (ReRAM) based analog in-memory-compute (IMC) coupled with spiking neural networks (SNN) offers a promising solution to implement efficient matrix multiplication. This work presents an ARM ...

Individuals with gait disorders are characterized by abnormalities in their walking pattern, adversely affecting their quality of life. For example, researchers have reported that individuals suffering from unilateral ...

Recent advances in next-generation biosensors are transforming on how infectious diseases are monitored and offering rapid, real-time, highly sensitive detection of pathogens. Emerging platforms such as wearable, ingestible, ...

This study investigates the deep learning-based rolling window approach in forecasting short-term solar PV generation. This study's primary objective is to develop a model for accurate short-term solar power forecasting ...

The sources of greenhouse gas emissions need to be replaced by renewable energy sources (RES) to reduce carbon emissions by 45% by 2030 and accomplish net zero by 2050, as proposed in the Paris Agreement. Microgrids have ...

Fiber Bragg grating (FBG)-based throat microphone's superior background noise suppression makes them ideal for wearable automatic speech recognition (ASR) devices. However, achieving naturalness and intelligibility remains ...

This work introduces a robust machine learning framework for modeling and optimizing the inner spacer etch process in gate-all-around FET fabrication. Using an in-house Particle Monte-Carlo simulator, the etch process is ...

Energy management systems (EMSs) are an integral part of power networks with distributed energy resources (DERs) for optimized energy transactions. Conventional EMS performs rule-based actions for energy transactions between ...

The diverse range of shapes enabled by modern nanofabrication techniques makes it challenging to identify the most optimal design for a desired optical response. While deep learning-based approaches are being increasingly ...

Logistics and transport industries face challenges in efficiently planning routes to minimize costs. The Vehicle Routing Problem (VRP) aims to optimize vehicle routes for customer deliveries. This study explores a heuristic ...