Abstract: Methods and devices are described that enable a device to generate a message including a multimodal composition, and to output the message on a device. The multimodal composition is generated by first selecting a first element belonging to a first output modality. The multimodal composition is further generated by selecting at least one second element belonging to a second output modality to associate with the first element, the combination of the first element and the second element being the multimodal composition.

Abstract: A duct includes a duct body defining an inlet, an outlet, and a channel connecting the inlet and the outlet. The duct body also defines an upstream resonator. The upstream resonator includes an upstream annular cavity external to the channel and an annular perforated plate coplanar with the upstream annular cavity. The duct body further defines a downstream resonator. The downstream resonator includes a downstream annular cavity external to the channel and an annular neck coplanar with the downstream annular cavity.

Abstract: A sound absorbing device includes a panel with an opening, a duct extending from the panel and in fluid communication with the opening, and a plurality of acoustic resonators embedded in the panel and in fluid communication with the duct. The duct can have a rectangular cuboid shape and the plurality of acoustic resonators can include a first subset of quarter-wavelength tubes extending from a first planar side of the duct, a second subset of quarter-wavelength tubes extending from a second planar side of the duct, a third subset of quarter-wavelength tubes extending from a third planar side of the duct, and a fourth subset of quarter-wavelength tubes extending from a fourth planar side of the duct. Also, the second subset of quarter-wavelength tubes and the fourth subset of quarter-wavelength tubes can have mirror symmetry with the first subset of quarter-wavelength tubes and the third subset of quarter-wavelength tubes, respectively.

Abstract: Methods and systems for deep learning alignment for semiconductor applications are provided. One method includes transforming design information for an alignment target on a specimen to a predicted image of the alignment target by inputting the design information into a deep learning model and aligning the predicted image to an image of the alignment target on the specimen generated by an imaging subsystem. The method also includes determining an offset between the predicted image and the image generated by the imaging subsystem based on results of the aligning and storing the determined offset as an align-to-design offset for use in a process performed on the specimen with the imaging subsystem.

Abstract: Systems and methods for determining the incident angle of an acoustic wave are presented herein. One embodiment receives an acoustic wave at N transducers, where N is a natural number greater than or equal to 2; solves a set of N coupled differential equations modeling a set of N virtual coupled acoustic resonators using N coupled analog circuits, wherein each of the N coupled analog circuits receives an output signal from a unique one of the N transducers and outputs a voltage signal; and analyzes the N voltage signals output by the N coupled analog circuits to produce an estimate of the incident angle of the acoustic wave.

Abstract: A method includes: pre-processing initial data of an acquired to-be-analyzed confrontation scenario, to obtain triplet data marked in a graph data structure, inputting the triplet data into a pre-trained analyzing model, to determine a result of analysis on semantic information of the to-be-analyzed confrontation scenario; wherein the analyzing model includes a plurality of operator networks that are provided with execution priorities, wherein the plurality of operator networks are configured for analyzing relations of different types; and the processing result of any one of the operator networks includes: in the relation type corresponding to the operator network, respective true relations of all of the node pairs, and confidences and descriptive values of the true relations; and according to the graph data structure that is updated by using the processing results of all of the operator networks, characterizing the result of analysis on the semantic information of the to-be-analyzed confrontation scenario.

Abstract: An automatic identification and classification production line for mobile terminal liquid crystal display (LCD) screens includes a size and posture identification adjustment part, a model identification part, and a classification storage device. The size and posture identification adjustment part can transport a mobile terminal LCD screen, identify front and back surfaces of the mobile terminal LCD screen, size of the mobile terminal LCD screen, and orientation of the mobile terminal LCD screen, and adjust the front surface of the mobile terminal LCD screen to face up and the orientation of the mobile terminal LCD screen to be the same as the transportation direction during transportation. The model identification part transports the mobile terminal LCD screen after adjustment of the posture, and identifies model of the mobile terminal LCD screen according to the size during transportation. The classification storage device classifies and stores mobile terminal LCD screens according to different models.