Abstract: An index modeling system that generates index models that predict values of an attribute of a supply chain for a commodity is disclosed. The index models are generated from indicator data that includes data related to multiple indicators and a plurality of sub-indicators of the index arranged in a hierarchical structure. Accordingly, the index values can be predicted for different entities at different levels in the hierarchical structure. The predicted index values can be used to automatically generate a filtered list of suppliers who can be used for procurement based on comparisons of the predicted attribute values of the suppliers with a predetermined attribute threshold value.

Abstract: Aspects of the present disclosure provide systems, methods, and computer-readable storage media that support automated failure mode detection for rotating machinery based on vibration analysis. To illustrate, a computing device may receive vibration data from one or more sensors configured to measure vibrations of a rotating machine, such as an engine. The computing device may generate a frequency spectrum based on the vibration data (or receive the frequency spectrum) and compare the frequency spectrum to one or more predetermined frequency models to determine one or more similarity metrics. The one or more predetermined frequency models may each be associated with a respective failure mode of the rotating machine. The computing device may identify a failure mode associated with a predetermined frequency model that corresponds to a similarity metric that satisfies a threshold, and the computing device may output an indication of the identified failure mode.

Abstract: A first device receives, via a blockchain node of the first device, data and constraints associated with a smart contract, where the smart contract is deployed via a blockchain node associated with a second device, the first and second devices are provided in a blockchain network, through their blockchain nodes. The first device provides, via the blockchain node, the data and constraints to an analytics engine of the first device, and performs, via the analytics engine, a data analytics technique on the data and constraints to generate an offer with optimized parameters. The first device provides the offer with the optimized parameters to the smart contract associated with the second device, and receives, via the blockchain node, a confirmation of a transaction associated with the smart contract. The first device causes the offer with the optimized parameters to be implemented based on receiving the confirmation of the transaction.

Abstract: A first device receives, via a blockchain node of the first device, data and constraints associated with a smart contract, where the smart contract is deployed via a blockchain node associated with a second device, the first and second devices are provided in a blockchain network, through their blockchain nodes. The first device provides, via the blockchain node, the data and constraints to an analytics engine of the first device, and performs, via the analytics engine, a data analytics technique on the data and constraints to generate an offer with optimized parameters. The first device provides the offer with the optimized parameters to the smart contract associated with the second device, and receives, via the blockchain node, a confirmation of a transaction associated with the smart contract. The first device causes the offer with the optimized parameters to be implemented based on receiving the confirmation of the transaction.