Abstract: The present disclosure describes devices and methods of providing a technology environment for analyzing unstructured data to generate structured data. A set of electronic documents, each electronic document associated with a type of product, may be accessed. A data instance for each of the documents may be generated. The data instance may include a plurality of data fields that are based on the type of product. The electronic documents may be analyzed to identify values for each of the plurality of data fields. Analyzing the electronic documents may comprise applying a respective character recognition algorithm to respective electronic documents, and assigning a confidence factor to each of the values. The data instances comprising the values for each of the plurality of data fields may be stored in a second database.

Abstract: Disclosed are techniques for using machine learning models to more reliably predict likelihoods of application failure. A model is trained to identify and display events that may cause high severity application failures. Logistic regression may be used to fit the model such that application features are mapped to a high severity event flag. Significant features of applications that relate to the high severity flag may be selected using stepwise regression. The identified applications may be displayed on a graphical user interface for review and reprioritization. Information may be ranked and displayed according to multiple different ranking criteria, such as one ranking generated by a first model, and another determined by one or more users. The multiple ranking criteria may be used to inform steps taken, and/or to retrain or tune the parameters of the model for subsequent predictions or classifications.

Abstract: Disclosed are techniques for using machine learning models to more reliably predict likelihoods of application failure. A model is trained to identify and display events that may cause high severity application failures. Logistic regression may be used to fit the model such that application features are mapped to a high severity event flag. Significant features of applications that relate to the high severity flag may be selected using stepwise regression. The identified applications may be displayed on a graphical user interface for review and reprioritization. Information may be ranked and displayed according to multiple different ranking criteria, such as one ranking generated by a first model, and another determined by one or more users. The multiple ranking criteria may be used to inform steps taken, and/or to retrain or tune the parameters of the model for subsequent predictions or classifications.

Abstract: The present disclosure describes devices and methods of providing a technology environment for analyzing unstructured data to generate structured data. A set of electronic documents, each electronic document associated with a type of product, may be accessed. A data instance for each of the documents may be generated. The data instance may include a plurality of data fields that are based on the type of product. The electronic documents may be analyzed to identify values for each of the plurality of data fields. Analyzing the electronic documents may comprise applying a respective character recognition algorithm to respective electronic documents, and assigning a confidence factor to each of the values. The data instances comprising the values for each of the plurality of data fields may be stored in a second database.

Abstract: The present disclosure describes devices and methods of providing a technology environment for analyzing unstructured data to generate structured data. A set of electronic documents, each electronic document associated with a type of product, may be accessed. A data instance for each of the documents may be generated. The data instance may include a plurality of data fields that are based on the type of product. The electronic documents may be analyzed to identify values for each of the plurality of data fields. Analyzing the electronic documents may comprise applying a respective character recognition algorithm to respective electronic documents, and assigning a confidence factor to each of the values. The data instances comprising the values for each of the plurality of data fields may be stored in a second database.

Abstract: A method for determining a load in a working machine including a linkage to be connected to an implement includes determining pressure in a first hydraulic cylinder and pressure in a second hydraulic cylinder arranged to control the linkage and determining at least one link angle between at least two links in the linkage. The method further includes, for a selected linkage bearing, determining at least two perpendicular force components acting on the selected linkage bearing, based on the determined pressure in each of the first and second cylinders and the at least one link angle; and determining a load on the selected linkage bearing as a linear combination of the at least two perpendicular force components using predetermined constants for the linear combination.

Abstract: A method for determining a load in a working machine including a linkage to be connected to an implement includes determining pressure in a first hydraulic cylinder and pressure in a second hydraulic cylinder arranged to control the linkage and determining at least one link angle between at least two links in the linkage. The method further includes, for a selected linkage bearing, determining at least two perpendicular force components acting on the selected linkage bearing, based on the determined pressure in each of the first and second cylinders and the at least one link angle; and determining a load on the selected linkage bearing as a linear combination of the at least two perpendicular force components using predetermined constants for the linear combination.