Abstract: There are provided solutions for multiagent debate. In a method, a first and a second response representation are determined by a first and a second agent in a plurality of agents based on a first query representation for a query in a natural language, respectively, and the first and second response representations are convertible to a first and a second answer to the query in the natural language, respectively. A second query representation is obtained based on the first query representation, and at least one of the first and second response representations. A response representation is determined based on the second query representation by at least one of the first and second agents, and the response representation is convertible to an answer to the query in the natural language. These agents communicate in an embedding space without a conversion between a natural language format and an embedding format.

Abstract: The present disclosure is directed to a mounting bracket adapted for adjusting the downtilt of an antenna. The mounting bracket includes a first member and a second member. The first member is coupled to the second member at one end via a first pair of securing features and is coupled to an antenna mounting bracket at an opposing end via a second pair of securing features. The first member is configured to rotate about the first and second pairs of securing features relative to the second member and antenna mounting bracket, respectively.

Abstract: A method for personalized intelligent wake-up system based on multimodal deep neural network comprises monitoring a sleeping status of a user; obtaining a current sleeping-stage of the user within a current time frame and a prediction of a next sleeping-stage of the user for a next time frame; correcting the current sleeping-stage of the user through combining the current sleeping-stage and the prediction of the next sleeping-stage; determining a wake up strategy for the current time frame; determining a relationship between each of a plurality of alarm impulses adopted to wake up the user and a corresponding reaction of the user; identifying a change in the current sleeping-stage for the current time frame; determining an alarm impulse to be triggered for waking up the user; and triggering the determined alarm impulse.

Abstract: A method for a scalable storage-loss optimized (SSLO) system for color gamut mapping is provided. The SSLO system method comprises generating a pre-computed color gamut mapping between an input color gamut and an output color gamut, receiving an input signal including a plurality of input pixels from the input signal domain, wherein the input pixels correspond to a set of first color values represented in a first color space; converting the set of the first color values to be a set of second color values represented in a second color space; generating a set of third color values through a mapping modeling and a color reproduction; converting the set of the third color values to be a set of fourth color values represented in the first color space; and outputting an output signal including a plurality of output pixels corresponding to the fourth color values to the output signal domain.

Abstract: A method for personalized intelligent wake-up system based on multimodal deep neural network comprises monitoring a sleeping status of a user; obtaining a current sleeping-stage of the user within a current time frame and a prediction of a next sleeping-stage of the user for a next time frame; correcting the current sleeping-stage of the user through combining the current sleeping-stage and the prediction of the next sleeping-stage; determining a wake up strategy for the current time frame; determining a relationship between each of a plurality of alarm impulses adopted to wake up the user and a corresponding reaction of the user; identifying a change in the current sleeping-stage for the current time frame; determining an alarm impulse to be triggered for waking up the user; and triggering the determined alarm impulse.

Abstract: A method for a scalable storage-loss optimized (SSLO) system for color gamut mapping is provided. The SSLO system method comprises generating a pre-computed color gamut mapping between an input color gamut and an output color gamut, receiving an input signal including a plurality of input pixels from the input signal domain, wherein the input pixels correspond to a set of first color values represented in a first color space; converting the set of the first color values to be a set of second color values represented in a second color space; generating a set of third color values through a mapping modeling and a color reproduction; converting the set of the third color values to be a set of fourth color values represented in the first color space; and outputting an output signal including a plurality of output pixels corresponding to the fourth color values to the output signal domain.