Results 141 to 150 of about 143,454 (291)
Abstract World markets for quality differentiated agri‐food products are highly competitive, presenting significant challenges for firms aiming to compete effectively. Government agencies and business organizations often implement various export promotion policies to address these challenges.
Nicolás Depetris‐Chauvin +1 more
wiley +1 more source
AI in chemical engineering: From promise to practice
Abstract Artificial intelligence (AI) in chemical engineering has moved from promise to practice: physics‐aware (gray‐box) models are gaining traction, reinforcement learning complements model predictive control (MPC), and generative AI powers documentation, digitization, and safety workflows.
Jia Wei Chew +4 more
wiley +1 more source
Estimation of Pico-Satellite Attitude Dynamics and External Torques via Unscented Kalman Filter
In this study, an Unscented Kalman Filter (UKF) algorithm is designed for estimating the attitude of a picosatellite and the in-orbit external disturbance torques.The estimation vector is formed by the satellite’s attitude, angular rates, and the unknown
Chingiz Hajiyev, Halil Ersin Söken
doaj
Environmental Disturbance Modelling for Future Gravity Missions [PDF]
Pelivan, I., Theil, S.
openaire +2 more sources
This review aims to provide a broad understanding for interdisciplinary researchers in engineering and clinical applications. It addresses the development and control of magnetic actuation systems (MASs) in clinical surgeries and their revolutionary effects in multiple clinical applications.
Yingxin Huo +3 more
wiley +1 more source
Quadrotor unmanned aerial vehicle control is critical to maintain flight safety and efficiency, especially when facing external disturbances and model uncertainties. This article presents a robust reinforcement learning control scheme to deal with these challenges.
Yu Cai +3 more
wiley +1 more source
Horizontal gravity disturbance vector in atmospheric dynamics
openaire +1 more source
Predicting Performance of Hall Effect Ion Source Using Machine Learning
This study introduces HallNN, a machine learning tool for predicting Hall effect ion source performance using a neural network ensemble trained on data generated from numerical simulations. HallNN provides faster and more accurate predictions than numerical methods and traditional scaling laws, making it valuable for designing and optimizing Hall ...
Jaehong Park +8 more
wiley +1 more source
Proactive Robotic Grasp Stability via Tactile Safety Margin Feedback
We introduce the tactile safety margin (TSM), defined as the ratio between applied friction force (Ffric) and maximum friction (Fmax) derived from grip force. A bilayer E‐skin with decoupled temperature, strain, and pressure sensing enables real‐time grasp stability monitoring through measured TSM values, allowing robots to proactively adjust grip ...
Yebin Park +10 more
wiley +1 more source
EMG‐Driven Telemetry and Inference System for Fish: Pose Reconstruction and Flow Sensing
This work introduces an electromyography (EMG)‐driven telemetry framework that reconstructs body pose and infers hydrodynamic conditions in freely swimming fish. A custom 16‐channel archival system records intramuscular EMG, enabling deep‐learning models to decode joint kinematics, classify flow regimes, and reveal channel‐efficient sensing strategies.
Rahdar Hussain Afridi +7 more
wiley +1 more source

