Abstract: A method, network node and wireless device for position reference signal (PRS) design by extending a base signal are disclosed. According to one aspect, a method in a wireless device (WD) includes obtaining extended reference signal, RS, configurations from the network node. The method also includes determining a waveform associated with the extended RS. The method also includes detecting a RS and estimate an associated time of arrival. The method further includes sending a measurement report to the network node based on the estimated time of arrival.

Abstract: The present disclosure provides an end-to-end proctoring system and method for conducting a secure online examination. The system comprises an image capturing device and an audio recording device for capturing and recording a plurality of live face images and a plurality of audio files of one or more users respectively. A processor is programmed to execute one or more module(s) stored in a memory, including, but not limited to, a user face recognition module, an occlusion detection module, a user authentication module, an object detection module, and an audio analytics module. The processor is further configured to control a warning module that may output a notification signal for the one or more module(s) when at least one suspicious activity is determined during the secure online examination. Further, the system with the processor for executing the one or more module(s) is pre-trained on various deep learning-based approaches for conducting a secure online examination.

Abstract: The present disclosure provides system and method for identification and classification of multilingual messages that would be considered inappropriate in an online interactive portal. The system may include processors to generate a set of data of intended inappropriate multilingual messages to train classification model. The set of data with labels is classified by assigning unique identifiers. The system includes pre-processing module to eliminate unwanted characters from set of data to train classification model. The classification model may be trained by multilingual representation module based at least in part on set of data with labels. The classification model determines whether set of data with one or more labels includes intended inappropriate multilingual messages. Furthermore, feedback loop module is utilised to retrain classification model recurrently to update set of data.