It’s happened to all of us: you find the perfect model for your needs — a bracket, a box, a cable clip, but it only comes in STL, and doesn’t quite fit. That problem will never happen if you’re using ...

Abstract: This letter proposes a novel hybrid method combining asymptotic waveform estimation (AWE), adaptive cross approximation (ACA), and efficient iterative method of moments–physical optics ...

Abstract: In this work, we propose a deep learning-based imaging method for addressing the multi-frequency electromagnetic (EM) inverse scattering problem (ISP). By combining deep learning technology ...

The challenge takes place from July 11-20 in designated South Florida locations. Participants compete for prizes, including $10,000 for removing the most pythons. Pythons must be killed humanely using ...

Every day, researchers search for optimal solutions. They might want to figure out where to build a major airline hub. Or to determine how to maximize return while minimizing risk in an investment ...

Linear solvers are major computational bottlenecks in a wide range of decision support and optimization computations. The challenges become even more pronounced on heterogeneous hardware, where ...

Neural networks are widely adopted in various fields due to their ability to model complex patterns and relationships. However, they face a critical vulnerability to adversarial attacks – small, ...

This repository contains a Python implementation of the Gauss-Seidel Elimination method for solving systems of linear equations. The code reads coefficients from an Excel file (`data.xls`), performs ...