Data are needed on the effect of oxygen delivered through a high-flow nasal cannula, as compared with standard oxygen therapy, on intubation and mortality in patients with acute hypoxemic respiratory ...

ABSTRACT: Surrogate-assisted evolutionary algorithms are widely used to solve expensive optimization problems due to their high search efficiency. However, a single model struggles to fit various ...

In a study published in Robot Learning journal, researchers propose a new learning-based path planning framework that allows mobile robots to navigate safely and efficiently using a Transformer model.

This project implements three fundamental navigation algorithms used in autonomous robotics, developed as part of my robotics engineering curriculum. The implementation uses ROS 2 (Robot Operating ...

Add Decrypt as your preferred source to see more of our stories on Google. Social media platform X has open-sourced its Grok-based transformer model, which ranks For You feed posts by predicting user ...

Abstract: Pathfinding is widely applied when encountering autonomous driving, mobile robot pathfinding, and so on. Traditional pathfinding algorithms have certain limitations such as high ...

Learn the Adagrad optimization algorithm, how it works, and how to implement it from scratch in Python for machine learning models. #Adagrad #Optimization #Python This is what happens when you drink ...

This repository contains my complete solutions to the legendary Karan's Mega Project List — a curated collection of programming challenges designed to improve coding skills across multiple domains.

For the low efficiency and poor generalization ability of path planning algorithm of industrial robots, this work proposes an adaptive field co-sampling algorithm (AFCS). Firstly, the environment ...

Abstract: Path optimization remains an issue of concern within the domain of the computer science gasoline, and in its use in the fields of robotics, logistics, network routing, or in the autonomous ...