Abstract: The present invention provides a GPS interference source positioning method, apparatus, electronic device, and readable storage medium, which relates to the technical field of wireless communications.

Abstract: A signal processing system and method for integrated communication and sensing includes a terminal and an access device. The terminal performs uplink transmission beamforming and management by using fused sensing information, and sends an uplink signal in an uplink time slot. The access device receives the uplink signal in the uplink time slot and receives an echo signal of a downlink signal in a downlink time slot; and performs incident angle estimation, performs reception beamforming and management, performs range and Doppler frequency shift estimation by using fused sensing information to obtain first sensing information of the uplink signal and second sensing information of the echo signal; updates the fused sensing information based on the first sensing information and the second sensing information; performs downlink transmission beamforming and management by using the fused sensing information, and sends a downlink signal in a downlink time slot.

Abstract: The present invention provides a GPS interference source positioning method, apparatus, electronic device, and readable storage medium, which relates to the technical field of wireless communications.

Abstract: A real-time detection method and apparatus for DGA domain name. An original domain name is translated into a multi-dimensional numeric vector, the multi-dimensional numeric vector is input into a deep learning model pre-trained based on an ImageNet data set, to generate a domain name feature, a domain name classifier is trained based on the generated domain name feature, and a DGA domain name is classified and predicted based on the domain name classifier obtained by training. The method firstly uses a deep learning model pre-trained based on an ImageNet data set, from the field of visual image classification and detection, for real-time detection of a DGA domain name, avoiding the process of high-intensity training and parameter weight adjustment for the deep learning model in DGA domain name detection. The detection rate is higher, and detection speed is faster.

Abstract: A real-time detection method and apparatus for DGA domain name. An original domain name is translated into a multi-dimensional numeric vector, the multi-dimensional numeric vector is input into a deep learning model pre-trained based on an ImageNet data set, to generate a domain name feature, a domain name classifier is trained based on the generated domain name feature, and a DGA domain name is classified and predicted based on the domain name classifier obtained by training. The method firstly uses a deep learning model pre-trained based on an ImageNet data set, from the field of visual image classification and detection, for real-time detection of a DGA domain name, avoiding the process of high-intensity training and parameter weight adjustment for the deep learning model in DGA domain name detection. The detection rate is higher, and detection speed is faster.

Abstract: A user activity detection engine monitors user activity during user sessions on a publication system, and detects a change in the level of the activity of the user that predicts that the user is about to execute a transaction. The change may be an increase in the level of activity. When the user activity detection engine detects such a change, the system may make an intervention to provide personalized marketing content for display to the user in an effort to improve the probability that the user will execute a transaction, and/or also to motive the user to execute the transaction on the system site instead of moving to a competitor site in search of a different transaction.

Abstract: A user activity detection engine monitors user activity during user sessions on a publication system, and detects a change in the level of the activity of the user that predicts that the user is about to execute a transaction. The change may be an increase in the level of activity. When the user activity detection engine detects such a change, the system may make an intervention to provide personalized marketing content for display to the user in an effort to improve the probability that the user will execute a transaction, and/or also to motive the user to execute the transaction on the system site instead of moving to a competitor site in search of a different transaction.