Abstract: A fan assembly includes a fan body, a motor-driven impeller contained within the fan body and arranged to generate an air flow, a nozzle including a nozzle body having an air inlet arranged to receive the air flow from the fan body, and one or more air outlets arranged to emit the airflow from the fan assembly. The fan assembly further includes a nozzle retaining mechanism for releasably retaining the nozzle on the fan body, and a rotation mechanism for rotating the nozzle body relative to the fan body. The nozzle rotation mechanism includes a rotation motor arranged to drive a drive member and a driven member that is arranged to be driven by the drive member to rotate around a rotation axis.

Abstract: A beverage system and methods for preparing flavored beverages are provided. In one embodiment, the beverage system includes a housing, a flavorant system, and a processor. The housing includes a mixing chamber configured to operably couple to a fluid reservoir and pressurized gas source. The processor is disposed in the housing and can be configured to cause, in response to at least one input, the separate dispensing of a fluid and a flavorant into a receptacle. The processor can also cause the delivery of gas from the pressurized gas source to the mixing chamber, where it can be used to form a carbonated fluid.

Abstract: A computer implemented method includes receiving a document with line item textual entries and an attachment containing images of different objects characterizing different transactions. The images of the different objects are split into individual image objects. Attributes from the individual image objects are extracted. The line item textual entries are matched with the individual image objects to form matched image objects. The matched image objects include ambiguous matches with multiple individual image objects assigned to a single line item textual entry or a single individual image object assigned to multiple line item textual entries. An assignment model is applied to resolve the ambiguous matches. The assignment model defines priority constraints, assigns pairs of line item textual entries and individual image objects that meet highest priority constraints, removes highest priority constraints when ambiguous matches remain, and repeats these operations until no ambiguous matches remain.

Abstract: A computer implemented method includes receiving a document with line item textual entries and an attachment containing images of different objects characterizing different transactions. The images of the different objects are split into individual image objects. Attributes from the individual image objects are extracted. The line item textual entries are matched with the individual image objects to form matched image objects. The matched image objects include ambiguous matches with multiple individual image objects assigned to a single line item textual entry or a single individual image object assigned to multiple line item textual entries. An assignment model is applied to resolve the ambiguous matches. The assignment model defines priority constraints, assigns pairs of line item textual entries and individual image objects that meet highest priority constraints, removes highest priority constraints when ambiguous matches remain, and repeats these operations until no ambiguous matches remain.