Delves into the energy-efficient distributed machine learning approach in the IoT era, emphasizing the importance of summarizing data for improved communication energy efficiency.
Explores finding reliable information, citing sources, and managing references in global health issues, emphasizing the importance of diversifying sources and validating information.
Covers the Nano-Tera Annual Plenary Meeting in Bern, showcasing innovative nanotechnology projects and cutting-edge developments in sensor nodes and semiconductor systems.
Covers wildfire susceptibility mapping using ML-Al robotics and various related topics, including experimental protocols, DFT feature engineering, SimpedCLIP, and Covid-19 detection.
Provides an overview of the Swiss Nanotera program, its achievements, ongoing research, and future directions in health, environment, and energy applications.
