Abstract: A method for dynamically controlling the alignment of multi-nested Objectives and Key Results (OKRs) is implemented via an application service provider server including a processor. The method includes executing, via a network, an enterprise application on a remote computing system and causing surfacing of a user interface on the display of the remote computing system during the execution of the enterprise application, where the user interface corresponds to a goal-setting feature of the enterprise application. The method also includes receiving, via the surfaced user interface, user input including an alignment permission policy for a multi-nested OKR of an enterprise, where the alignment permission policy defines a list of enterprise users who are allowed to align child OKR objects to a parent objective of the multi-nested OKR. The method further includes applying the alignment permission policy to the multi-nested OKR.

Abstract: Systems and methods for efficient presentation of payment options at point of sale devices are disclosed. A method may include: identifying a plurality of stored or provisioned payment cards in customer wallets for a merchant; (2) pre-qualifying each of the customers associated with the stored/provisioned payment cards for one or more installment payment options for a purchase from the merchant; and (3) communicating a list of token reference identifiers for stored/provisioned payment cards that have been pre-qualified and the one or more pre-qualified installment payment options to a merchant computer program executed by a merchant backend, wherein the merchant computer program receives a token reference identifier for a stored or provisioned payment card in one of the customer wallets, determines that the token reference identifier is on the list of pre-qualified token reference identifiers, and presents the one or more installment payment options in a checkout user interface.

Abstract: An example computing device may include memory and one or more processors. The one or more processors may be configured to parallel entropy decode encoded video data from a received bitstream to generate entropy decoded data. The one or more processors may be configured to predict a motion vector based on the entropy decoded data. The one or more processors may be configured to decode a motion vector residual from the entropy decoded data. The one or more processors may be configured to add the motion vector residual and motion vector. The one or more processors may be configured to warp previous reconstructed video data with an overlapped block-based warp function using the motion vector to generate predicted current video data. The one or more processors may be configured to sum the predicted current video data with a residual block to generate current reconstructed video data.

Abstract: Techniques are described for performing transformation on video data. A transform circuit may receive M sample values of the video data from a pre-transform buffer, and process the M sample values with N computation units of the transform circuit to generate intermediate values. Processing the M sample values to generate the intermediate values includes feeding back temporary values from output of one or more of the N computation units to input of one or more of the N computation units. The transform circuit may store a first set of the intermediate values in a transpose buffer, and store a second set of the intermediate values in the pre-transform buffer that are to be later retrieved for storage in the transpose buffer.

Abstract: Methods, systems, and devices for motion analysis are described. Generally, the described techniques provide for computationally efficient and accurate motion analysis. A device may identify frames of a video frame sequence having a defined resolution. The device may downscale the frames to generate a plurality of downsampled images each having a resolution lower than the defined resolution. The device may generate a respective histogram vector for each pixel of each downsampled image and each pixel of the original frames. The device may determine a motion vector candidate based at least in part on the histogram vectors. The device may apply a filter to the motion vector candidates to determine a final motion vector and output an indication of motion between the frames of the video frame sequence based at least in part on the final motion vector for each pixel of the second frame.

Abstract: Techniques are described for performing transformation on video data. A transform circuit may receive M sample values of the video data from a pre-transform buffer, and process the M sample values with N computation units of the transform circuit to generate intermediate values. Processing the M sample values to generate the intermediate values includes feeding back temporary values from output of one or more of the N computation units to input of one or more of the N computation units. The transform circuit may store a first set of the intermediate values in a transpose buffer, and store a second set of the intermediate values in the pre-transform buffer that are to be later retrieved for storage in the transpose buffer.