A fish-quality determination system (1) analyzes, through machine learning, a relationship among image data taken of cross-sections of tails of fish, boat data indicating fishing boats that caught the fish, and quality data indicating quality of the fish. When having acquired, from a user device (3), image data of a cross-section of the tail of a fish subject to determination and boat data indicating a fishing boat that caught the fish, the system (1) uses, as an input, the image data of the cross-section of the tail of the fish subject to the determination and the boat data indicating the fishing boat that caught the fish that have been acquired so as to estimate and output quality of the fish subject to the determination on the basis of the analyzed relationship. The output quality of the fish subject to the determination is displayed on the user device (3).

A method comprises receiving a route of an aircraft, identifying a plurality of service providers to provide data services for the aircraft based on the route, receiving data from the plurality of service providers associated with the data services, transmitting the data received from the plurality of service providers to the aircraft, determining a total amount associated with all of the data services provided by the plurality of service providers, and transmitting information on the total amount associated with all of the data services provided by the plurality of service providers.

The present disclosure relates to systems and methods for pharmaceutical injection supply management, and in particular, recommending an optimal amount of pharmaceutical injection supply for a user to load into a dispenser. Implementations of the systems and methods discussed herein can provide, via a mobile application, a recommendation to a pharmaceutical user of the amount of substance to load into their substance pump during a site change. The recommendation can be optimized to minimize substance costs and substance waste, or to accommodate a target replacement date and time.

Embodiments of systems and methods for the aggregation, analysis, display and monetization of pricing data for commodities in general, and which may be particularly useful applied to vehicles are disclosed. Specifically, in certain embodiments, historical transaction data associated with a particular vehicle configuration may be obtained and processed to determine pricing data associated with the vehicle configuration. The historical transaction data or determined pricing data may then be presented in an intuitive manner.

Embodiments of systems and methods for the aggregation, analysis, display and monetization of pricing data for commodities in general, and which may be particularly useful applied to vehicles are disclosed. Specifically, in certain embodiments, historical transaction data associated with a particular vehicle configuration may be obtained and processed to determine pricing data associated with the vehicle configuration. The historical transaction data or determined pricing data may then be presented in an intuitive manner.

An information processing apparatus according to the present application includes an acquiring unit and a deciding unit. The acquiring unit acquires attribute information on a user. The deciding unit decides, based on the attribute information acquired by the acquiring unit, a placement position in which a virtual riding point that corresponds to a riding point that is used for the user to ride in a moving vehicle and that is virtually set is placed.

An information processing apparatus according to the present application includes an acquiring unit and a deciding unit. The acquiring unit acquires attribute information on a user. The deciding unit decides, based on the attribute information acquired by the acquiring unit, a placement position in which a virtual riding point that corresponds to a riding point that is used for the user to ride in a moving vehicle and that is virtually set is placed.

When a process of returning a vehicle is performed, a fee setting device identifies a zone where the vehicle is returned, and calculates the identified zone's zone SOC. The fee setting device determines whether a discount for leveling is applicable. The fee setting device compares a zone SOC of a zone where a user rented a vehicle and a zone SOC of a zone where the user returned the vehicle. When the zone SOC of the zone where the user rented the vehicle is larger than the zone SOC of the zone where the user returned the vehicle, the discount for leveling is applied.

A method of traffic reduction in a mesh computing system (400), the mesh computing system (400) comprising hosts located on edge nodes of the mesh computing system (400) and a central registry located outside the mesh computing system (400), the central registry holding the images. The method comprises, at a first host located at a first edge node, receiving (920) a request from a client for an image, sending (930) a request for the image to at least one other host of the mesh computing system (400). When the first host receives (940) notification that at least a second host holds the image, the first host downloads (960) the image from the second host to the first host. The first host creates (970) a container from the image. A host at a node (636; 700) and a mesh computing system (400) are also provided.

A management server is configured to perform a process including: a step of obtaining a utilization history of each user in the previous month when a condition for performing a dividing ratio setting process is satisfied; a step of updating a utilization record evaluation; a step of calculating a first dividing ratio; a step of updating a driving record evaluation; a step of calculating a second dividing ratio; and a step of setting a dividing ratio.