Drones guide smarter nitrogen use in tobacco fields

Balancing nitrogen use is critical for maximizing crop yield while minimizing environmental and economic costs. A new approach integrates drone-based multispectral imaging with machine learning to ...
IEEE

Adaptive Impedance Learning for Robots Interacting With Unknown Environments via Streaming Sparse Gaussian Processes

Abstract: Impedance control with fixed parameters lacks the flexibility to adapt to dynamic and uncertain environments, which may not meet the task requirements during robot-environment interaction.
PC Tech Magazine

Inside the AI Systems That Catch Fake Clicks in Real Time

Ad fraud is no longer a fringe issue. It is a systemic threat to digital advertising, and its scale demands a technological ...

The Car as a Space of Silence: How Modern Vehicles Create New Privacy in a Public World

Inside the quiet revolution redefining how we experience solitude, focus, and identity on the road In the midst of ...
Military.com

Army xTechHumanoid Competition Highlights Aptima’s Fully Autonomous Robot Mobility Research

Aptima reached the Army xTechHumanoid finals with a fully autonomous locomotion system that helps humanoid robots navigate ...
Scientific Research Publishing

A Spatio-Temporal Prediction Model for Wall Turbulence Based on Hybrid Neural Networks ()

The spatio-temporal evolution of wall-bounded turbulence is characterized by high nonlinearity, multi-scale dynamics, and chaotic nature, making its accurate prediction a significant challenge for ...
Scientific Research Publishing

A Lightweight Self-Supervised Representation Learning Framework for Depression Risk Profiling from Synthetic Daily Behavioural Trajectories ()

Detecting behavioural signatures of depression from everyday digital traces is a central challenge in computational psychiatry. Real-world datasets from smartphones and wearables often suffer from ...