Abstract: An example operation may include one or more of generating a hashed summary including hashes of one or more of a validation data set and hashes of data points chosen in previous iterations from producer nodes, and exposing the hashed summary to a plurality of producer nodes, receiving, iteratively, a plurality of requests from the plurality of producer nodes, respectively, where each request identifies a marginal value provided by a hash of a data sample available to a producer node, selecting a request received from a producer node based on a marginal value associated with the request, retrieving hashed data of the producer node associated with the selected request, and aggregating the hashed data of the producer node with the summary of hashes generated at one or more previous iterations to produce an updated summary, and storing the updated summary via a data block of a distributed ledger.

Abstract: An example operation may include one or more of acquiring, by a retailer node, an inventory data from a supplier node over a blockchain network, receiving, by the retailer node, outstanding orders data of the supplier node, generating, by the retailer node, an order distribution policy based on the inventory data and the outstanding orders data, and executing a smart contract to order goods from the supplier node based on the ordering policy.

Abstract: An example operation may include one or more of acquiring, by a retailer node, an inventory data from a supplier node over a blockchain network, receiving, by the retailer node, outstanding orders data of the supplier node, generating, by the retailer node, an order distribution policy based on the inventory data and the outstanding orders data, and executing a smart contract to order goods from the supplier node based on the ordering policy.

Abstract: An example operation may include one or more of receiving, by a first node, a freshness of goods data from a second node over a blockchain, and executing, by the first node, a smart contract to: calculate an initial order quantity based on a pre-set critical order number and a non-expiring goods order quantity and alter a final order quantity based on the initial order quantity and the freshness of the goods data.

Abstract: An example operation may include one or more of receiving, by a retailer node, an encrypted inventory of goods data from a plurality of supplier nodes over a blockchain network, computing, by the retailer node, an ordering proportion based on the encrypted inventory of goods data, generating, by the retailer node, an ordering policy based on the ordering proportion, and executing a smart contract to order goods from the plurality of the supplier nodes based on the ordering policy.

Abstract: Techniques for mapping policy documents to regulatory documents to check for compliance between the policies and documents are provided. In one example, a computer-implemented method determining, by a system operatively coupled to a processor, an information input, a control framework, and a document from a first group consisting of a regulatory document and a policy document, wherein the information input is a corpora from a second group consisting of a domain corpora and a global corpora. The computer-implemented method can also comprise mapping, by the system, the received regulatory document or the received policy document to the control framework using a supervised machine learning technique.

Abstract: An example operation may include one or more of receiving, by a resolver node, from at least one user node assets to be recorded on a blockchain, executing, by the resolver node, a smart contract to reject non-conforming assets from being stored on the blockchain based on a set of rules defined by an asset validation format, determining, by the resolver node, events and transactions related to the rejected assets, and allowing the at least one user node to tag the rejected assets, the events and the transactions related to the rejected assets as contradictory.

Abstract: An example operation may include one or more of receiving, by a retailer node, an encrypted inventory of goods data from a plurality of supplier nodes over a blockchain network, computing, by the retailer node, an ordering proportion based on the encrypted inventory of goods data, generating, by the retailer node, an ordering policy based on the ordering proportion, and executing a smart contract to order goods from the plurality of the supplier nodes based on the ordering policy.

Abstract: An example operation may include one or more of receiving a data file submitted by a node, the data file comprising information about an event-driven process for a chain of nodes, retrieving an entitlement mode of the data file from a data block that is stored among a hash-linked chain of data blocks on a distributed ledger, determining access rights of the data file with respect to another node in the chain of nodes based on the retrieved entitlement mode of the data file, and transmitting information about the event-driven process to the other node based on the determined access rights of the other node.

Abstract: An example operation may include one or more of releasing, by a subscription service node, at least one blockchain transaction to a plurality of subscribing blockchain nodes requiring direct entitlement access, executing, by the subscription service node, a smart contract to calculate secondary entitlements triggered by the at least one blockchain transaction, determining, by the subscription service node, portions of second entitlement data sets allowed to be accessed by a subset of the plurality of the subscribing blockchain nodes, and sending verification data to the plurality of the subscribing blockchain nodes for verification of the second entitlement data sets.

Abstract: An example operation includes one or more of traversing, by a modeling node, a supply-chain downstream from an initial step, detecting, by a modeling node, a multi-organization step, and responsive to the detection of the multi-organization step, executing a branch prediction algorithm to determine downstream granted organizations.

Abstract: An example operation may include one or more of receiving, by a retailer node, an encrypted inventory of goods data from a plurality of supplier nodes over a blockchain network, computing, by the retailer node, an ordering proportion based on the encrypted inventory of goods data, generating, by the retailer node, an ordering policy based on the ordering proportion, and executing a smart contract to order goods from the plurality of the supplier nodes based on the ordering policy.

Abstract: There is provided a method for managing a solid state storage system with hybrid storage technologies. The method includes monitoring one or more storage request streams to identify operating mode characteristics therein from among a set of possible operating mode characteristics. The set of possible operating mode characteristics correspond to a set of available operating modes of the hybrid storage technologies. The method further includes identifying a current operating mode from among the set of available operating modes responsive to the identified operating mode characteristics. The method also includes predicting a likely future operating mode responsive to variations in workload requirements to generate at least one future operating mode prediction. The method additionally includes controlling at least one of data placement, wear leveling, and garbage collection, responsive to the at least one future operating mode prediction.

Abstract: A computer implemented method of improving parameters of a critic approximator module includes receiving, by a mixed integer program (MIP) actor, (i) a current state and (ii) a predicted performance of an environment from the critic approximator module. The MIP actor solves a mixed integer mathematical problem based on the received current state and the predicted performance of the environment. The MIP actor selects an action a and applies the action to the environment based on the solved mixed integer mathematical problem. A long-term reward is determined and compared to the predicted performance of the environment by the critic approximator module. The parameters of the critic approximator module are iteratively updated based on an error between the determined long-term reward and the predicted performance.

Abstract: An example operation may include one or more of receiving, by a retailer node, an encrypted inventory of goods data from a plurality of supplier nodes over a blockchain network, computing, by the retailer node, an ordering proportion based on the encrypted inventory of goods data, generating, by the retailer node, an ordering policy based on the ordering proportion, and executing a smart contract to order goods from the plurality of the supplier nodes based on the ordering policy.

Abstract: There is provided a method for managing a solid state storage system with hybrid storage technologies. The method includes monitoring one or more storage request streams to identify operating mode characteristics therein from among a set of possible operating mode characteristics. The set of possible operating mode characteristics correspond to a set of available operating modes of the hybrid storage technologies. The method further includes identifying a current operating mode from among the set of available operating modes responsive to the identified operating mode characteristics. The method also includes predicting a likely future operating mode responsive to variations in workload requirements to generate at least one future operating mode prediction. The method additionally includes controlling at least one of data placement, wear leveling, and garbage collection, responsive to the at least one future operating mode prediction.

Abstract: An example operation may include one or more of collecting, by a first node, a plurality of permissioned data inputs from a plurality of second nodes of a supply-chain, performing, by the first node, a granular simulation based on the permissioned data inputs to generate a plurality of key performance indicators (KPIs), and executing a smart contract to adjust order processes of the supply-chain based on the KPIs.

Abstract: An example operation includes one or more of detecting a fork in a supply-chain by a modeling node, resolving, by the modeling node, a branch prediction to determine a likely access control, generating, by the modeling node, a range of information based on a branch confidence level, and responsive to the resolution of the branch prediction, revoking access from a document or granting a greater access to the document based on the range.

Abstract: An example operation may include one or more of receiving, by a first node, from a second node at least one document describing an action performed on assets of an asset supply-chain at a location of the second node, executing, by the first node, a smart contract to translate the at least one document into a standardized form of entry and exit events and to define containment relationship of the assets, and computing metrics on the asset supply-chain based on the standardized form and the containment relationship.

Abstract: Techniques for outside-in mapping for corpus pairs are provided. In one example, a computer-implemented method comprises: inputting first keywords associated with a first domain corpus; extracting a first keyword of the first keywords; inputting second keywords associated with a second domain corpus; generating an embedded representation of the first keyword via a trained model and generating an embedded representation of the second keywords via the trained model; and scoring a joint embedding affinity associated with a joint embedding.