Abstract: An embodiment for learning-based automatic selection of artificial intelligence applications. The embodiment may receive a user request for an exam, the user request including exam information. The embodiment may automatically identify an exam type cluster corresponding to the received exam information. The embodiment may automatically detect applicable AI applications corresponding to the identified exam type cluster. The embodiment may automatically run each applicable AI application on a series of relevant test sets to generate a score for each applicable AI application. The embodiment may automatically recommend to a user a highest-scoring applicable AI application.

Abstract: Systems, methods, and computer-program products for fluid analysis and monitoring are disclosed. Embodiments include a removable and replaceable sampling system and an analytical system connected to the sampling system. A fluid may be routed through the sampling system and data may be collected from the fluid via the sampling system. The sampling system may process and transmit the data to the analytical system. The analytical system may include a command and control system to receive and store the data in a database and compare the data to existing data for the fluid in the database to identify conditions in the fluid. Fluid conditions may be determined using machine learning models that are generated from well-characterized known training data. Predicted fluid conditions may then be used to automatically implement control processes for an operating machine containing the fluid.

Abstract: Systems, methods, and computer-program products for fluid analysis and monitoring are disclosed. Embodiments include a removable and replaceable sampling system and an analytical system connected to the sampling system. A fluid may be routed through the sampling system and data may be collected from the fluid via the sampling system. The sampling system may process and transmit the data to the analytical system. The analytical system may include a command and control system to receive and store the data in a database and compare the data to existing data for the fluid in the database to identify conditions in the fluid. Fluid conditions may be determined using machine learning models that are generated from well-characterized known training data. Predicted fluid conditions may then be used to automatically implement control processes for an operating machine containing the fluid.

Abstract: Systems, methods, and computer-program products for fluid analysis and monitoring are disclosed. Embodiments include a removable and replaceable sampling system and an analytical system connected to the sampling system. A fluid may be routed through the sampling system and data may be collected from the fluid via the sampling system. The sampling system may process and transmit the data to the analytical system. The analytical system may include a command and control system to receive and store the data in a database and compare the data to existing data for the fluid in the database to identify conditions in the fluid. Fluid conditions may be determined using machine learning models that are generated from well-characterized known training data. Predicted fluid conditions may then be used to automatically implement control processes for an operating machine containing the fluid.

Abstract: Embodiments of the present disclosure provide for systems, apparatuses, and methods for real-time fluid analysis. Embodiments include a removable and replaceable sampling system and an analytical system connected to the sampling system. A fluid may be routed through the sampling system and real-time data may be collected from the fluid via the sampling system. The sampling system may process and transmit the real-time data to the analytical system. The analytical system may include a command and control system that may receive and store the real-time data in a database and compare the real-time data to existing data for the fluid in the database to identify conditions in the fluid.

Abstract: Systems, methods, and computer-program products for fluid analysis and monitoring are disclosed. Embodiments include a removable and replaceable sampling system and an analytical system connected to the sampling system. A fluid may be routed through the sampling system and data may be collected from the fluid via the sampling system. The sampling system may process and transmit the data to the analytical system. The analytical system may include a command and control system to receive and store the data in a database and compare the data to existing data for the fluid in the database to identify conditions in the fluid. Fluid conditions may be determined using machine learning models that are generated from well-characterized known training data. Predicted fluid conditions may then be used to automatically implement control processes for an operating machine containing the fluid.

Abstract: Systems, methods, and computer-program products for fluid analysis and monitoring are disclosed. Embodiments include a removable and replaceable sampling system and an analytical system connected to the sampling system. A fluid may be routed through the sampling system and data may be collected from the fluid via the sampling system. The sampling system may process and transmit the data to the analytical system. The analytical system may include a command and control system to receive and store the data in a database and compare the data to existing data for the fluid in the database to identify conditions in the fluid. Fluid conditions may be determined using machine learning models that are generated from well-characterized known training data. Predicted fluid conditions may then be used to automatically implement control processes for an operating machine containing the fluid.

Abstract: Systems, methods, and computer-program products for fluid analysis and monitoring are disclosed. Embodiments include a removable and replaceable sampling system and an analytical system connected to the sampling system. A fluid may be routed through the sampling system and data may be collected from the fluid via the sampling system. The sampling system may process and transmit the data to the analytical system. The analytical system may include a command and control system to receive and store the data in a database and compare the data to existing data for the fluid in the database to identify conditions in the fluid. Fluid conditions may be determined using machine learning models that are generated from well-characterized known training data. Predicted fluid conditions may then be used to automatically implement control processes for an operating machine containing the fluid.

Abstract: Embodiments of the present disclosure provide for systems, apparatuses, and methods for real-time fluid analysis. Embodiments include a removable and replaceable sampling system and an analytical system connected to the sampling system. A fluid may be routed through the sampling system and real-time data may be collected from the fluid via the sampling system. The sampling system may process and transmit the real-time data to the analytical system. The analytical system may include a command and control system that may receive and store the real-time data in a database and compare the real-time data to existing data for the fluid in the database to identify conditions in the fluid.

Abstract: The present disclosure provides systems, apparatuses, and methods for fluid analysis. Embodiments include a removable and replaceable sampling system and an analytical system connected to the sampling system. A fluid may be routed through the sampling system and real-time data may be collected from the fluid via the sampling system. The sampling system may process and transmit the real-time data to the analytical system. The analytical system may include a command and control system that may receive and store the real-time data in a database and compare the real-time data to existing data for the fluid in the database to identify conditions in the fluid.

Abstract: Systems, methods, and computer-program products for fluid analysis and monitoring are disclosed. Embodiments include a removable and replaceable sampling system and an analytical system connected to the sampling system. A fluid may be routed through the sampling system and data may be collected from the fluid via the sampling system. The sampling system may process and transmit the data to the analytical system. The analytical system may include a command and control system to receive and store the data in a database and compare the data to existing data for the fluid in the database to identify conditions in the fluid. Fluid conditions may be determined using machine learning models that are generated from well-characterized known training data. Predicted fluid conditions may then be used to automatically implement control processes for an operating machine containing the fluid.

Abstract: Systems, methods, and computer-program products for fluid analysis and monitoring are disclosed. Embodiments include a removable and replaceable sampling system and an analytical system connected to the sampling system. A fluid may be routed through the sampling system and data may be collected from the fluid via the sampling system. The sampling system may process and transmit the data to the analytical system. The analytical system may include a command and control system to receive and store the data in a database and compare the data to existing data for the fluid in the database to identify conditions in the fluid. Fluid conditions may be determined using machine learning models that are generated from well-characterized known training data. Predicted fluid conditions may then be used to automatically implement control processes for an operating machine containing the fluid.

Abstract: Embodiments of the present disclosure provide for systems, apparatuses, and methods for real-time fluid analysis. Embodiments include a removable and replaceable sampling system and an analytical system connected to the sampling system. A fluid may be routed through the sampling system and real-time data may be collected from the fluid via the sampling system. The sampling system may process and transmit the real-time data to the analytical system. The analytical system may include a command and control system that may receive and store the real-time data in a database and compare the real-time data to existing data for the fluid in the database to identify conditions in the fluid.

Abstract: A method and system for using a rebate card are disclosed. The method may comprise initiating a purchase transaction for one or more products at a point of sale, determining whether the purchase transaction qualifies for a rebate, determining a rebate value based on the purchase transaction and the rebate, activating a rebate value in a rebate card account associated with a rebate card based on the determining action, and delivering the rebate card to a customer of the one or more products during the purchase transaction.

Abstract: A method and system for using a rebate card are disclosed. The method may comprise initiating a purchase transaction for one or more products at a point of sale, determining whether the purchase transaction qualifies for a rebate, determining a rebate value based on the purchase transaction and the rebate, activating a rebate value in a rebate card account associated with a rebate card based on the determining action, and delivering the rebate card to a customer of the one or more products during the purchase transaction.

Abstract: Methods for using a rebate card and preventing the retention of rebate value when the product that prompted the rebate is returned are disclosed. Methods for using the rebate card may be limited for use at a particular retailer and/or for a particular manufacturer's goods or services. Methods for preventing the improper retention of rebate value may comprise: determining the amount the customer paid for the product; determining if a rebate value was provided for the product being returned; deducting the amount of the rebate from the amount the customer paid for the product; and providing the remaining amount the customer paid for the product being returned to the customer. In some embodiments of the present invention, the amount of the rebate value that was provided based on the purchase of the product being returned may be deducted from the customer's rebate account. Additionally, rebate cards may be RFID enabled.

Abstract: A first person can give a gift by using a mobile phone or other communications device to access a central computing system to which a gift and a second person (the intended recipient of the gift) can be identified by the first person. Thereafter, the central computing system transmits a unique code to the mobile phone or other communications device of the second person. The code can then be given by the second person, verbally or by transmission or display by his/her mobile phone, to a retailer of the gift. Upon validation by the retailer, such as by communication between the retailer's point-of-sale system and the central computing system, the retailer provides the gift identified by the first person.

Abstract: A method and system for using a rebate card are disclosed. The method may comprise initiating a purchase transaction for one or more products at a point of sale, determining whether the purchase transaction qualifies for a rebate, determining a rebate value based on the purchase transaction and the rebate, activating a rebate value in a rebate card account associated with a rebate card based on the determining action, and delivering the rebate card to a customer of the one or more products during the purchase transaction.

Abstract: The invention is directed to a system and method for managing a payment system. The method generally comprises activating a payment card, associating a value with the payment card, associating at least one third party with the bill payment card, receiving a request from a bill payment card user to transfer at least some of the value to a selected third party, the request comprising receiving an identifier associated with the payment card and receiving an indication of an amount of value to transfer, and transferring at least some of the value to the selected third party. Systems of the invention may generally comprise one or more payment cards, a database storing a plurality of records comprising information related to the payment card; one or more communication devices; and a processor in communication with the database and in selective communication with the communication device.

Abstract: A method for using a temporary value card is provided. A first value is determined base upon a selection of goods or services from a provider. The temporary value card is sold at a POS. The first value is associated with the temporary value card.