Researchers at the Leibniz Institute of Photonic Technology (Leibniz IPHT) in Jena, Germany, together with international ...

This study introduces a blockchain-based covert communication model utilizing dynamic Base-K encoding. The proposed encoding scheme utilizes the input address sequence to determine K to encode the ...

Chaotic communication systems and signal processing represent a cutting‐edge field where the inherent unpredictability of non-linear dynamics is harnessed for robust, efficient data transmission ...

Active vision dynamically refines spatiotemporal neural representations, optimising visual processing through scanning behaviour and non-associative learning, providing insights into efficient sensory ...

Imagine a world where every smart device, from traffic sensors to wearable health monitors, can seamlessly communicate. This vision is at the heart of Massive Machine Type Communication (mMTC), a ...

James W. Dearing ([email protected]) is a professor in the Department of Communication at Michigan State University, in East Lansing. Jeffrey G. Cox is a research associate in the Department of ...

Recent advances in machine learning have shown that deep neural networks (DNNs) can provide powerful and flexible models of neural sensory processing. In the auditory system, standard linear-nonlinear ...

The IMF paper introduces a powerful multilingual AI model that quantifies central bank communication across 169 institutions from 1884 to 2025, analyzing tone, stance, audience, and sentiment. It ...

Learn how MCP’s standardized framework simplifies AI tool collaboration, eliminates custom integrations, and boosts ...

Inspired by naturally occurring air bubbles in glaciers, researchers have developed a method to encode messages in ice.