IEEE

On Improving Accuracy of Implicit FDTD Methods with Transformer-based Deep Learning Network

Abstract: The implicit Finite-Difference Time-Domain (FDTD) methods represent a class of algorithms that alleviate or even eliminate the Courant–Friedrich-Lev (CFL) stability condition inherent in ...
IEEE

On Improving Accuracy of Implicit FDTD Methods With Transformer-Based Deep Learning Network

Abstract: The implicit finite-difference time-domain (FDTD) methods represent a class of algorithms that alleviate or even eliminate the Courant–Friedrich–Levy (CFL) stability condition inherent in ...
GitHub

2D Finite-Difference Time-Domain (FDTD) electromagnetic field solver — built in Python.

The Finite-Difference Time-Domain method is a numerical technique for solving Maxwell's equations directly in the time domain. Instead of approximating solutions analytically, FDTD discretizes space ...
Investopedia

Understanding the 72(t) Rule: Penalty-Free IRA Withdrawals Explained

Julia Kagan is a financial/consumer journalist and former senior editor, personal finance, of Investopedia. Investopedia / Dennis Madamba Rule 72(t) allows penalty-free withdrawals from individual ...
Frontiers

Retraction: Novel microstructural features on heat and mass transfer in peristaltic flow through a curved channel

The journal retracts the 9 June 2020 article cited above. Following publication, the publisher has found evidence that the peer review process was compromised. As the scientific integrity of the ...
GitHub

Automata-Based Token Recognition System

This project implements a token recognition system using finite automata theory for lexical analysis in compiler design. The system reads source code and divides it into small parts called tokens, ...