Physics-informed neural networks (PINNs) are an increasingly powerful way to solve partial
differential equations, generate digital twins, and create neural surrogates of physical models…

Although we see many advancements in voice-enabled technologies, there is an acute disparity
between speech-based human-machine interface technologies (eg speech to text) and …

… When output is between 1 and 5 V, the gated clock generator made with nand gates is disabled.
… Author wishes to acknowledge JT Vinchhi for his help in wiring of the circuit and to NPM …

… NAND gate (A18) becomes zero and disables the gated clock generator. The clock generator
frequency is 900Hz and is built with NAND … Jayaraman for his suggestions, Mr JT Vinchhi …

jinns is an open-source Python library for physics-informed neural networks, built to tackle
both forward and inverse problems, as well as meta-model learning. Rooted in the JAX …

Julia has been heralded as a potential successor to Python for scientific machine learning
and numerical computing, boasting ergonomic and performance improvements. Since Julia's …

A third-order sigma-delta modulator with the architecture of cascade of integrator feedback (CIFB)
is proposed for an analog-digital converter used in low-power sensor interfaces. It …

Einstein field equations are notoriously challenging to solve due to their complex mathematical
form, with few analytical solutions available in the absence of highly symmetric systems …

This research introduces a novel anomaly detection method designed to enhance the
operational reliability of particle accelerators - complex machines that accelerate elementary …

Differentiable programming is a new paradigm for modeling and optimization in many fields
of science and engineering, and automatic differentiation (AD) algorithms are at the heart of …