Abstract: Systems and methods for providing an archive of precedents are provided. The archive of precedents includes determining precedent data; parsing a new-event XML file for string data, wherein the string data is related to a new event; generating a vector embedding from the string data; determining a similar embedding in a vector space, wherein the similar embedding is a vector embedding of an instance of precedent data; parsing XML files of the precedent and new event and using parsed data to generate an old-to-new value map; retrieving the corresponding XML file and the corresponding precedent-event document associated with the vector embedding of the instance of precedent data; and providing, as input to a natural language processing model, the list of text strings recovered from the editable form of the document of the precedent event and the old-to-new value map.

Abstract: A method of generating a structural model architecture, comprising receiving an input causality map, including: a plurality of variables, one or more links providing an indication of influence between pairs of variables, wherein at least one link provides an indication of influence between an input variable and at least one other variable; and one or more constraints associated with one or more of the variables and/or links, and generating an architecture for a structural model based on the input causality map, the structural model configured to predict a value of an output variable based on a value of at least one other variable in the plurality of variables.

Abstract: Systems and methods for providing an archive of precedents are provided. The archive of precedents includes determining precedent data; parsing a new-event XML file for string data, wherein the string data is related to a new event; generating a vector embedding from the string data; determining a similar embedding in a vector space, wherein the similar embedding is a vector embedding of an instance of precedent data; parsing XML files of the precedent and new event and using parsed data to generate an old-to-new value map; retrieving the corresponding XML file and the corresponding precedent-event document associated with the vector embedding of the instance of precedent data; and providing, as input to a natural language processing model, the list of text strings recovered from the editable form of the document of the precedent event and the old-to-new value map.

Abstract: Automated evaluation and improvement of code quality is disclosed. A method may include: receiving code to optimize; evaluating the code for a plurality of code quality dimensions using a LLM, wherein the LLM returns a code quality score and a qualitative summary for each code quality dimension; generating an overall code quality score based on the code quality score and the qualitative summary; improving the code using the LLM based on the code quality score and the qualitative summary for each code quality dimension; evaluating the improved code for the plurality of code quality dimensions using the wherein the LLM returns an updated code quality score and an updated qualitative summary; generating an overall code quality score based on the updated code quality score and the updated qualitative summary; and outputting the improved code in response to the updated code quality score being higher than the overall code quality score.

Abstract: In some aspects, the techniques described herein relate to a method including: receiving, at an alarm management service, a plurality of alarms, wherein each of the plurality of alarms includes respective alarm data; clustering the plurality of alarms into an alarm cluster group; generating a plurality of binary time sequences, wherein each of the plurality of binary time sequences corresponds to one of the plurality of alarms; generating an initial alarm graph based on the alarm cluster group and the plurality of binary time sequences; providing, as input to a causal inference process, the initial alarm graph and the plurality of binary time sequences; and generating, by the causal inference process, a causal alarm graph, wherein the causal alarm graph is a partially connected and directed graph.

Abstract: Systems and methods for providing an archive of precedents are provided. The archive of precedents includes determining precedent data; parsing a new-event XML file for string data, wherein the string data is related to a new event; generating a vector embedding from the string data; determining a similar embedding in a vector space, wherein the similar embedding is a vector embedding of an instance of precedent data; parsing XML files of the precedent and new event and using parsed data to generate an old-to-new value map; retrieving the corresponding XML file and the corresponding precedent-event document associated with the vector embedding of the instance of precedent data; and providing, as input to a natural language processing model, the list of text strings recovered from the editable form of the document of the precedent event and the old-to-new value map.

Abstract: A method of generating a structural model architecture, comprising receiving an input causality map, including: a plurality of variables, one or more links providing an indication of influence between pairs of variables, wherein at least one link provides an indication of influence between an input variable and at least one other variable; and one or more constraints associated with one or more of the variables and/or links, and generating an architecture for a structural model based on the input causality map, the structural model configured to predict a value of an output variable based on a value of at least one other variable in the plurality of variables.

Abstract: Disclosed is a system for executing a data access transaction. The system comprises a server arrangement, the server arrangement being communicably coupled with at least one requesting device and at least one responding device. The server arrangement is configured to receive from a requesting device and a responding device, a first data and a second data respectively, wherein the first data and the second data are encrypted and temporally defined.

Abstract: Disclosed is a system, method and computer program for executing a data access transaction. The system comprises a server arrangement, communicably coupled with a requesting device(s) and a responding device(s). The server arrangement is configured to receive from the requesting device and the responding device, first data and second data respectively, wherein the first data and the second data are encrypted. Further, metadata of the first data is received from the requesting device; and an encrypted association score is determined by comparing the first data and the second data, wherein the encrypted association score is based at least on a dynamic evaluation component, wherein the dynamic evaluation component includes a causality measure.

Abstract: Disclosed is a system for executing a data access transaction. The system comprises a server arrangement, the server arrangement being communicably coupled with at least one requesting device and at least one responding device. The server arrangement is configured to receive from a requesting device and a responding device, a first data and a second data respectively, wherein the first data and the second data are encrypted and temporally defined.

Abstract: Disclosed is a system for executing a data access transaction. The system comprises a server arrangement, the server arrangement being communicably coupled with at least one requesting device and at least one responding device. The server arrangement is configured to receive from a requesting device and a responding device, a first data and a second data respectively, wherein the first data and the second data are encrypted and temporally defined.