Balancing nitrogen use is critical for maximizing crop yield while minimizing environmental and economic costs.

Abstract: To improve the control performance of permanent magnet synchronous motor (PMSM) drive systems, this article proposes a model-free predictive current control method based on adaptive extended ...

Advances in machine learning and shape-memory polymers are enabling engineers to design for mechanical performance first and ...

Farming is changing from manual, experience-led observation to data-driven decision-making powered by advanced sensing systems and artificial intelligence. A new research paper titled “Fast Forward ...

Abstract: IMU-based motion capture systems face challenges of attitude drift and magnetic interference. To address these, this paper proposes a hybrid algorithm named AMI-IAGDA, which integrates an ...

Accurate colour reproduction is one of the most technically demanding challenges in industrial imaging. Unlike monochrome applications, colour imaging requires the entire imaging chain, from lighting ...

Affinity combines a comprehensive set of photo editing, page layout, and vector illustration tools into a single, free app, ...

Imaging-based single-cell physiological profiling holds great potential for uncovering fundamental bacterial cold shock response (CSR) mechanisms, but its application is impeded by severe focus drift ...

More engineers are turning to reinforcement learning to incorporate adaptive and self-tuning control into industrial systems. It aims to strike a balance between traditional ...

To enable more accurate estimation of connectivity, we propose a data-driven and theoretically grounded framework for optimally designing perturbation inputs, based on formulating the neural model as ...

Researchers have developed an advanced artificial intelligence (AI) framework designed to significantly improve the forecasting of carbon dioxide emissions in the aviation sector. ACGRIME is an ...