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DXMaps.com presents a dynamic, real-time mapping service for amateur radio DX spots, integrating data from traditional DX clusters, _PSK Reporter_, and WSPR networks. The platform visually plots global QSO and SWL activity, enabling users to observe propagation conditions across various bands, from 2200m to >450 MHz. It offers distinct overlays such as the magnetic equator, gray line, moon footprint for EME, and VOACAP propagation predictions, providing a comprehensive view of radio wave behavior. The service allows granular filtering of displayed spots, including options to show only DX-Cluster data, PSK Reporter activity, or WSPR signals. Users can refine the map view by selecting specific bands (e.g., 160m, 20m, 6m, 2m), limiting spots to the last 15 minutes, or displaying only contacts exceeding **2600 km**. Additional features include the ability to toggle grid squares, aurora forecasts, and various amateur radio zones (CQ, ITU). Distinctively, the resource updates automatically every minute, ensuring current propagation intelligence without manual refresh. It also supports specialized views for EME, ionospheric scatter, and aircraft scatter, alongside FM DX and APRS activity. The platform emphasizes the importance of accurate locator information in DX spots to enhance data quality and offers a user manual and FAQ for guidance.

Shortwave listeners and amateur radio operators interested in _numbers stations_ can engage with this mailing list, which serves as a platform for discussing the enigmatic transmissions. The resource facilitates the exchange of information regarding these unusual broadcasts, often associated with intelligence agencies, by allowing members to share observations, decode attempts, and theories. It provides a community space for those who monitor the HF spectrum for these unique, often automated, voice or digital signals. Participation on the list enables members to contribute to a collective understanding of numbers station activity, including changes in frequencies, broadcast schedules, and message formats. While specific technical analysis or signal processing techniques are discussed by members, the primary function is information sharing. The list is administered by csmolinski at blackcatsystems.com, and prior postings are archived for reference, allowing new members to review historical discussions and data.

How to use AI (Artificial Intelligence) to identify Radio signals using a RTL SDR dongle and Linux (Ubuntu). This solution implement a framework using Keras and TensorFlow to learn and recognize the RF signals.