Abstract In this paper, we focus on the detection and localization of radioactive sources by exploiting supervised machine learning. Machine learning is utilized in a wide variety applications due to its effectiveness prediction autonomous decision-making. However, applying would only be effective when representative features for application can acquired, through which algorithms trained. Hence...

Although microseisms have been observed for more than 100 years, the precise locations of their excitation sources in oceans are still elusive. Underwater Distributed Acoustic Sensing (DAS) brings new opportunities to study microseism generation mechanisms. Using DAS data off coast Valencia, Spain, and applying a cross-correlation approach, we show that high-frequency (0.5–2 Hz) confined betwee...

Current data storage, retrieval, and management mechanisms are inherently complex, perpetuating the need for intuitive access to stored data. The Internet has complicated the situation further by vastly increasing the quantity, types, and availability of data. In a distributed environment, data storage, retrieval, and management must coordinate among multiple heterogeneous sources. In this arti...