Abstract: Embodiments are described herein that involve a computing device initiating playback of a particular media item on a media playback system that is registered to a particular account of a social media service. The computing device may query the social media service for one or more accounts of the social media service that are registered to respective media playback systems that have played the particular media item on at least a threshold number of occasions and have not yet been connected to the particular account of the social media service within the social network. The computing device may receive the queried one or more accounts of the social media service and cause a graphical interface to display one or more respective selectable indications of the received one or more accounts of the social media service.

Abstract: This application is directed to predicting vehicle turn and brake actions for at least partially autonomous vehicle driving. A first vehicle obtains a plurality of images along a road. For each image of the plurality of images, the first vehicle extracts, from the image, a plurality of image regions each corresponding to a respective vehicle light of a second vehicle positioned on the road near the first vehicle. The first vehicle generates, for each image, a composite image that includes the plurality of image regions. The first vehicle determines, for each image region, a probability that a respective vehicle light of the second vehicle changed its state. The first vehicle predicts a vehicle action of the second vehicle based on the probability for each image region. The first vehicle at least partially autonomously driving the first vehicle based on the predicted vehicle action of the second vehicle.

Abstract: Systems and methods are provided for risk management in an expert system. A distribution of feature values within a training dataset for the expert system and each of a plurality of baseline datasets are determined, and Kullback-Leibler divergences between the baseline dataset and the training dataset to provide set of Kullback-Leibler divergence values. Measures of central tendency and statistical dispersion of the set of Kullback-Leibler divergence values are determined, and a threshold Kullback-Leibler divergence value is determined from these values and a desired confidence interval for new datasets. A Kullback-Leibler divergence value between the feature values of novel dataset and the training dataset is determined and it is determined that the second dataset represents an unacceptable divergence if this Kullback-Leibler divergence value exceeds the threshold value.

Abstract: In some embodiments, apparatuses and methods are provided herein useful for access token conversion. The system comprises a first application programming interface (API) backend using a first authentication service based on a first tokenization protocol and a second API backend using a second authentication service based on a second tokenization protocol. The second authentication service is configured to receive from, a user device, a call to the second API backend with a first token associated with the first authentication service, convert the first token to a first converted token based on the second tokenization protocol, and forward the first converted token to the user device for use in subsequent calls to the second API backend.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to multichannel authentication and tokenization. A system comprises a first authentication system serving a plurality of in-store point of sale terminals and implementing a physical channel authentication policy and a second authentication system serving a plurality of user devices accessing an e-commerce service and implementing an e-commerce channel authentication policy, and a tokenization system. The tokenization system being configured to generate a first token in response to receiving a first user credential from an in-store point of sale terminal via the first authentication system, generate a second token in response to receiving a second user credential from a user device via the second authentication system, and forward the first token and the second token to the retailer backend system, wherein the first token and the second token are generated based on a same tokenization protocol.

Abstract: Systems and methods are provided for evaluating a maintenance report. A maintenance report is received for an item of modular industrial equipment. The maintenance report includes a maintenance-related code, selected from a defined library of maintenance-related codes, and a free text field describing either or both of an observation of the item of modular equipment that is inconsistent with a defined specification and an action taken to repair or maintain the item of modular industrial equipment. A plurality of features representing the semantic content of a free-text field are extracted, with at least a portion of the plurality of features being extracted via a document embedding approach. At an expert system, a new maintenance-related code is determined from the defined library of maintenance-related codes for the item of modular industrial equipment, from the plurality of features.

Abstract: One example includes a forecasting inventory management system for a fleet of assets. An I/O interface receives inputs defining inventory and supply chain parameters of the assets and component(s) of each asset over a duration of time spanning from a present time to a future time. The inputs further include a time-phased input corresponding to a change associated with at least one of the inventory and supply chain parameters at future time(s) in the duration of time. The I/O interface can also provide outputs comprising an inventory assessment model comprising an allocation of the inventory of the component(s) throughout the duration of time. A memory system stores a database defining the inventory and supply chain parameters associated with the assets and the component(s). A forecasting engine generates the inventory assessment model at the present time based on the inventory and supply chain parameters throughout the duration of time.