Abstract: Systems, devices, and methods are provided for using an automated assessment and evaluation of machine translations. A system may receive a request associated with translating first content from a first language to a second language. The system may translate the first content from the first language to the second language. The system may determine an attribute associated with the first content. The system may determine a translation score associated with second content translated from the first language to the second language and associated with the attribute, the translation score indicative of a machine translation accuracy. The system may determine, and based on the translation score, a translation protocol, and may execute the translation protocol.

Abstract: A testing system computer device for dynamically updating a test plan of an apparatus includes at least one processor in communication with at least one memory device. The testing system computer device is configured to store a plurality of historical data and generate a simulation model of the apparatus based in part on the historical data. The simulation model includes a plurality of inputs and a plurality of outputs of the apparatus. The testing system computer device is also configured to determine a plurality of tests to perform on the apparatus based on the simulation model and the plurality of historical data. The testing system computer device is further configured to receive a plurality of desirability ratings from a user, rank the plurality of tests to perform based on the plurality of desirability ratings, and present the ranked plurality of tests to the user.

Abstract: Some aspects are directed to data reconciliation frameworks. An example framework is configured to receive core data, the system model comprising a plurality of data records associated with at least two assets, receive a system model, the system model comprising context data indicating, execute a configuration operation of a data validation process based on the system model, execute the data validation process to identify at least one inconsistent or incomplete record among the plurality of data records, determine at least one data reconciliation technique from a plurality of data reconciliation techniques based on the system model, and apply the at least one data reconciliation technique to the core data to reconcile the at least one inconsistent or incomplete record.

Abstract: A testing system computer device for dynamically updating a test plan of an apparatus includes at least one processor in communication with at least one memory device. The testing system computer device is configured to store a plurality of historical data and generate a simulation model of the apparatus based in part on the historical data. The simulation model includes a plurality of inputs and a plurality of outputs of the apparatus. The testing system computer device is also configured to determine a plurality of tests to perform on the apparatus based on the simulation model and the plurality of historical data. The testing system computer device is further configured to receive a plurality of desirability ratings from a user, rank the plurality of tests to perform based on the plurality of desirability ratings, and present the ranked plurality of tests to the user.

Abstract: Some aspects are directed to data reconciliation frameworks. An example framework is configured to receive core data, the system model comprising a plurality of data records associated with at least two assets, receive a system model, the system model comprising context data indicating, execute a configuration operation of a data validation process based on the system model, execute the data validation process to identify at least one inconsistent or incomplete record among the plurality of data records, determine at least one data reconciliation technique from a plurality of data reconciliation techniques based on the system model, and apply the at least one data reconciliation technique to the core data to reconcile the at least one inconsistent or incomplete record.

Abstract: A system for similarity analysis-based information augmentation for a target component includes an information augmentation (IA) computer device. The IA computer device identifies a target component input variable with unavailable data. The IA computer device executes a similarity analysis function, identifying at least two test components with data for the input variable exceeding a threshold. The IA computer device generates parameter distributions for test data for each test component. The IA computer device generates model coefficients using the parameter distributions, determining a proportional mix of the parameter distributions. The IA computer device authors a predictive model configured to generate at least one predicted value for the target data for the at least one input variable for the target component by including the at least one model coefficient in the predictive model. The IA computer device generates, using the predictive model, the at least one predicted value.