A new study introduces a global probabilistic forecasting model that predicts when and where ionospheric disturbances—measured by the Rate of total electron content (TEC) Index (ROTI)—are likely to ...

Multifidelity optimization can inform decision-making during process development and reduce the number of experiments ...

Abstract: Gaussian process regression (GPR) models are becoming increasingly tightly integrated into robotic systems, particularly in the context of robot model predictive control (MPC) operating in ...

Virtuix Inc. (NASDAQ: VTIX), a developer of full-body virtual reality systems, is taking things to the next level, having ...

Please follow these steps to install the repository and the required libraries: first, clone the repository along with its submodules; then, create the environment ...

The EcoBOT platform was developed, which consists of sterile containers (EcoFABs) for growing plants and imaging for monitoring plant growth and health. Brachypodium distachyon was grown on the EcoBOT ...

This important work introduces a family of interpretable Gaussian process models that allows us to learn and model sequence-function relationships in biomolecules. These models are applied to three ...

ABSTRACT: The study applies a Kalman filter (KF) to Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models to create a hybrid model, to estimate the parameters of the GARCH model in ...

Xgrids has launched LCC for Revit, a new plug-in that brings SLAM-based 3D Gaussian Splatting technology directly into Autodesk Revit workflows. According to the company, the technology delivers 70-90 ...

Abstract: Accurate time series forecasting is crucial for optimizing resource allocation, industrial production, and urban management, particularly with the growth of cyber-physical and IoT systems.

Developing novel materials drives significant breakthroughs across various engineering fields. Recent advancements in computational resources and techniques have enabled comprehensive material ...