Abstract: A network topology is provided that includes multiple data centers for building blockchain blocks. The data centers can process different subgroups of blocks, and then send updates to one another with information about new blocks. Additionally, some data centers may protect sensitive block body information, and instead may only share block headers.

Abstract: A method for verifying that event can take place before the event is executed is disclosed. A verification system is incorporated into an event processing network, such that the verification system can identify newly proposed events and determine whether they can be completed. The verification system can inform the network about verification results through distributed blockchain records. Other changes in event status can also be communicated through and stored in blockchain records.

Abstract: A method for verifying that event can take place before the event is executed is disclosed. A verification system is incorporated into an event processing network, such that the verification system can identify newly proposed events and determine whether they can be completed. The verification system can inform the network about verification results through distributed blockchain records. Other changes in event status can also be communicated through and stored in blockchain records.

Abstract: A method for tracking multiple classes of records in a single blockchain is disclosed. Class identifiers can used for each record entry to distinguish between classes within the blockchain.

Abstract: A method for tracking multiple classes of records in a single blockchain is disclosed, the method comprising: by the administrative node computer, receiving, from a first node computer, a request for a class identifier for a certain class, the request including an address identifier associated with the first node computer; generating the class identifier; creating an association between the class identifier and the address identifier; receiving a data element from the first node computer, the data element including the address identifier, the class identifier, and record update information; verifying that the class identifier is associated with the address identifier; verifying that the record update information is permitted according to the class identifier; and creating, a block for a blockchain, the block including the data element. Class identifiers can used for each record entry to distinguish between classes within the blockchain.

Abstract: A computer-implemented method for automated forecasting of cash flow includes: monitoring, while a plurality of first transactions are being processed in a payment network, payable transaction data associated with the plurality of first transactions, the plurality of first transactions initiated with at least one account issued to a merchant; monitoring, while a plurality of second transactions are being processed in a payment network, receivable transaction data associated with the plurality of second transactions, the plurality of second transactions between the merchant and a plurality of users; determining, based on the payable transaction data and the receivable transaction data, a plurality of seasonal variables; and generating a cash flow forecast associated with the merchant, the cash flow forecast generated based on the plurality of seasonal variables. A system and computer program product for automated forecasting of cash flow are also disclosed.

Abstract: A method for combining multiple interactions into a single record entry is disclosed. A data package can be created that represents a set of interactions, and each entity associated with an interaction can review the data package. Each entity can indicate agreement with the interactions by digitally signing the data package. Once signed by each involved entity, the data package can be stored in a record such as a blockchain.

Abstract: A network topology is provided that includes multiple data centers for building blockchain blocks. The data centers can process different subgroups of blocks, and then send updates to one another with information about new blocks. Additionally, some data centers may protect sensitive block body information, and instead may only share block headers.

Abstract: A network topology is provided that includes multiple data centers for building blockchain blocks. The data centers can process different subgroups of blocks, and then send updates to one another with information about new blocks. Additionally, some data centers may protect sensitive block body information, and instead may only share block headers.

Abstract: A method for providing interactive recording networks is disclosed. Multiple child networks can be established, each child network being coordinated by a respective coordinating entity. Each coordinating entity can also participate in a central parent network. A data package can be sent from one network to another. When a data package is sent to another network, additional data can be added to indicate that the data package is being escalated.

Abstract: A network topology is provided that includes multiple data centers for building blockchain blocks. The data centers can process different subgroups of blocks, and then send updates to one another with information about new blocks. Additionally, some data centers may protect sensitive block body information, and instead may only share block headers.

Abstract: A method for tracking multiple classes of records in a single blockchain is disclosed, the method comprising: by the administrative node computer, receiving, from a first node computer, a request for a class identifier for a certain class, the request including an address identifier associated with the first node computer; generating the class identifier; creating an association between the class identifier and the address identifier; receiving a data element from the first node computer, the data element including the address identifier, the class identifier, and record update information; verifying that the class identifier is associated with the address identifier; verifying that the record update information is permitted according to the class identifier; and creating, a block for a blockchain, the block including the data element. Class identifiers can used for each record entry to distinguish between classes within the blockchain.

Abstract: A method for verifying that event can take place before the event is executed is disclosed. A verification system is incorporated into an event processing network, such that the verification system can identify newly proposed events and determine whether they can be completed. The verification system can inform the network about verification results through distributed blockchain records. Other changes in event status can also be communicated through and stored in blockchain records.

Abstract: A method including identifying a customer when the customer uses a television service; storing contents that are each tagged with a Myers-Briggs Type Indicator or one or more personality characteristics pertaining to a Myers-Briggs Type Indicator; selecting contents from the stored contents; providing a user interface to permit the customer to choose from a selection of the stored contents to rate; receiving ratings of a chosen contents from the customer; identifying the customer's Myers-Briggs Type Indicator based on the received ratings; and providing the customer's Myers-Briggs Type Indicator to the customer.

Abstract: A method of reducing boundary effect in a THz-CT image includes correcting steering of the THz beam and/or Fresnel reflection prior to reconstruction of the THz image, the method including tomographically scanning an object at selected rotational positions to obtain a plurality of projection slices, and prior to reconstructing the THz-CT image using a Radon transformation, applying to each of the plurality of projection slices an algorithm to determine a location of left and right edges of the object relative to the center of rotation of the object, determining a range of values for which the measured attenuation is not instrument limited based on a maximum detectable attenuation, and applying a further algorithm representing the corrected attenuation projection array data which will be inverted using the Radon transformation, the algorithm including an experimentally measured attenuation, correction for beam steering, and accounting for Fresnel reflection loss at the incident and exiting air-object interface

Abstract: A method storing information that indicates similarity between contents based on content metadata associated with each content, wherein a degree of similarity between contents is based on a semantic interpretation of plot metadata included in content metadata and pertaining to each plot associated with each content; receiving a search query from a user; retrieving one or more content metadata pertaining to one or more contents based on the search query; retrieving one or more recommended content metadata pertaining to one or more recommended contents that are similar to the one or more content metadata pertaining to the one or more contents based on the stored information; and providing a search result that includes the one or more content metadata and the one or more recommended content metadata via a user interface.

Abstract: A method including identifying a customer when the customer uses a television service; storing contents that are each tagged with a Myers-Briggs Type Indicator or one or more personality characteristics pertaining to a Myers-Briggs Type Indicator; selecting contents from the stored contents; providing a user interface to permit the customer to choose from a selection of the stored contents to rate; receiving ratings of a chosen contents from the customer; identifying the customer's Myers-Briggs Type Indicator based on the received ratings; and providing the customer's Myers-Briggs Type Indicator to the customer.

Abstract: A method storing information that indicates similarity between contents based on content metadata associated with each content, wherein a degree of similarity between contents is based on a semantic interpretation of plot metadata included in content metadata and pertaining to each plot associated with each content; receiving a search query from a user; retrieving one or more content metadata pertaining to one or more contents based on the search query; retrieving one or more recommended content metadata pertaining to one or more recommended contents that are similar to the one or more content metadata pertaining to the one or more contents based on the stored information; and providing a search result that includes the one or more content metadata and the one or more recommended content metadata via a user interface.