Abstract: A method for determining a correctness of an actually received timestamp is provided. A communication network includes a master clock, a first ECU having a first slave clock, a validator having a second slave clock, and a first communication bus. The first ECU uses a first communication standard having a deterministic scheme. The method includes synchronizing, at the first ECU, a time of the first slave clock to a global time of the master clock, synchronizing, at the validator, a time of the second slave clock to the global time of the master clock, predicting, at the validator, a timestamp to be received in an actual communication cycle from the first ECU based on the deterministic scheme of the communication standard used by the first ECU, and comparing, at the validator, the predicted timestamp with the actually received timestamp from the first ECU.

Abstract: A system for root cause analysis based on process optimization data is provided. The system receives log data associated with a first trace between a first activity and a second activity of a process. The system further determines a state of inefficiency between the first activity and the second activity based on the received log data. The system further applies a first machine learning (ML) model on the received log data. The system further determines a first label and a first value to be associated with the first trace of the process based on the application of the first ML model. The system further generates presentation data associated with the determined state of inefficiency of the first trace based on the determination of the first label and the first value and further transmits the generated presentation data on a user device.

Abstract: Exemplary system and method embodiments described and shown herein are directed to optimizing warehouse picking operations. Exemplary system and method embodiments employ order allocation optimization and/or order grouping optimization that are individually or collectively usable to allocate and group warehouse orders in a manner that minimizes picker travel and maximizes labor productivity.

Abstract: An embodiment may involve a server-side log collected by a server device, where the server-side log includes a set of entries indicating a unique identifier, and wherein the unique identifier is assigned to a work item of a server-based application executed by the server device. The embodiment may further involve one or more processors configured to: receive, from a client device disposed upon a network, a client-side log, wherein the client-side log includes operational data related to usage of a client-based application executed by the client device; identify, from the operational data, the client-based application and one or more activities performed by the client-based application; determine that the one or more activities are related to the unique identifier; based on the one or more activities, determine an action that can be taken to improve efficacy of the server-based application; and write, to the persistent storage, a representation of the action.

Abstract: A skills ontology includes classes of data that define skills possessed or demonstrated by employees of an enterprise. Specifically, sets of data may be received and segmented into strings of text referred to as utterances. The utterances may be provided to an NLU service/engine, which uses NLU techniques to process the utterances to extract intents and/or entities. Skills may be identified from within the extracted entities. New skill records may be added to the skills ontology for newly extracted skills. Employee profiles of the skills ontology may also be updated based on the actions being performed. Further, the skills ontology may be utilized to identify employees having the skills associated with tasks to be performed and assign the task to an employee for completion. Once the task as been completed, skills profiles of the employee in the skills ontology may be updated to reflect performance of the task.

Abstract: Provided is a method for determining a correctness of image data, the image data being captured by at least two cameras of a camera system installed at a vehicle. The method includes detecting at least one feature in the image data captured by a first one of the at least two cameras, determining if the at least one feature can be detected in the image data captured by a second one of the at least two cameras, and if the at least one feature can be detected in the image data captured by the second one of the at least two cameras, determining the correctness of the image data.

Abstract: An example embodiment may involve identifying local traces of related events within a plurality of event data repositories, wherein each of the event data repositories is respectively associated with a software application; using a clustering model, assigning the local traces into clusters; determining positive rules that define when pairs of the local traces are linked to a common global trace, and negative rules that define when the pairs are linked to different global traces; linking the pairs into global traces; iteratively training a similarity model to project the local traces into a vector space such that the pairs that are linked to common global traces exhibit a greater similarity with one another than the pairs that are linked to different global traces; and based on the similarity model as trained, linking further local traces to the global traces.

Abstract: At least service task data and application utilization data are collected. The collected data is analyzed to determine a utilization pattern. Based on the determined utilization pattern, a computer automation opportunity is automatically identified. An automatically generated recommendation of an automation solution among a plurality of automation solution candidates is provided for the identified computer automation opportunity.

Abstract: Exemplary system and method embodiments described and shown herein are directed to optimizing warehouse picking operations. Exemplary system and method embodiments employ order allocation optimization and/or order grouping optimization that are individually or collectively usable to allocate and group warehouse orders in a manner that minimizes picker travel and maximizes labor productivity.

Abstract: A method includes sending, from the master controller to the slave controller, a follow up message in response to a pull of a predefined pin, wherein the follow up message includes a global time of the master controller when the predefined pin was pulled; sending, from the slave controller to the master controller, a validation message in response to the received follow up message, wherein the validation message includes a global time of the slave controller when the pull of the predefined pin is detected by the slave controller; and validating the time synchronization by checking, at the master controller and/or the slave controller, if a difference between the global time of the master controller when the predefined pin was pulled and the global time of the slave controller when the pull of the predefined pin is detected by the slave controller is smaller than a predefined first threshold.

Abstract: An embodiment may involve a server-side log collected by a server device, where the server-side log includes a set of entries indicating a unique identifier, and wherein the unique identifier is assigned to a work item of a server-based application executed by the server device. The embodiment may further involve one or more processors configured to: receive, from a client device disposed upon a network, a client-side log, wherein the client-side log includes operational data related to usage of a client-based application executed by the client device; identify, from the operational data, the client-based application and one or more activities performed by the client-based application; determine that the one or more activities are related to the unique identifier; based on the one or more activities, determine an action that can be taken to improve efficacy of the server-based application; and write, to the persistent storage, a representation of the action.

Abstract: A method for determining a correctness of an actually received timestamp is provided. A communication network includes a master clock, a first ECU having a first slave clock, a validator having a second slave clock, and a first communication bus. The first ECU uses a first communication standard having a deterministic scheme. The method includes synchronizing, at the first ECU, a time of the first slave clock to a global time of the master clock, synchronizing, at the validator, a time of the second slave clock to the global time of the master clock, predicting, at the validator, a timestamp to be received in an actual communication cycle from the first ECU based on the deterministic scheme of the communication standard used by the first ECU, and comparing, at the validator, the predicted timestamp with the actually received timestamp from the first ECU.

Abstract: An example embodiment may involve identifying local traces of related events within a plurality of event data repositories, wherein each of the event data repositories is respectively associated with a software application; using a clustering model, assigning the local traces into clusters; determining positive rules that define when pairs of the local traces are linked to a common global trace, and negative rules that define when the pairs are linked to different global traces; linking the pairs into global traces; iteratively training a similarity model to project the local traces into a vector space such that the pairs that are linked to common global traces exhibit a greater similarity with one another than the pairs that are linked to different global traces; and based on the similarity model as trained, linking further local traces to the global traces.

Abstract: An embodiment includes storage containing configuration and operational data related to a managed network, an action configurator application, and an action execution application. The embodiment also includes one or more processors configured to: receive, by way of the action configurator application, a specification of an action type; receive, by way of the action configurator application, a specification of an input source for actions generated using the action type; receive, by way of the action configurator application, a specification of one or more target users and an output modality for the actions; receive, by way of the action configurator application, a specification of a condition that causes the actions to be generated; determine, that the condition has been satisfied; and cause the action execution application to execute the action generator on the input source, and produce an output for one of the target users by way of the output modality.

Abstract: A remote network management platform may include persistent storage containing: (i) data related to a managed network, and (ii) a persona of a user. The remote network management platform may also include a platform application associated with a web-based user interface and using a portion of the data. The remote network management platform may also include a recommendation engine with access to a set of rules or a machine learning (ML) model corresponding to the platform application. The recommendation engine may be configured to: (i) read, from the persistent storage, the portion of the data and the persona; (ii) apply, to the portion of the data and the persona, the set of rules or the ML model to generate one or more recommendations; and (iii) transmit, by way of the web-based user interface and to the user, representations of the one or more recommendations.

Abstract: An embodiment involves receiving a request specifying a particular process, wherein an event table associates event identifiers of events, process identifiers of processes that generated to the events, timestamps of times when the events occurred, states of the processes at the times, and references to related processes; generating nodes of a graph, wherein the particular process and each of its related processes are represented by entity nodes annotated with respective process identifiers, and the events are represented by event nodes annotated with respective event identifiers; generating edges between the entity nodes and the event nodes for which the events of the event nodes either were: generated by the processes represented by the entity nodes, or refer to the processes represented by the entity nodes; and generating edges between pairs of the event nodes that: generated by a common process, and the events of which occurred sequentially according to their timestamps.

Abstract: A method for performing time-synchronization between a master clock of a master unit and a plurality of slave clocks of a corresponding plurality of slave units includes sending a forward time-synchronization message indicative of the master clock from the master unit to the plurality of slave units, in order to enable the plurality of slave units to time-synchronize their respective slave clocks with the master clock. The method also includes receiving a reverse time-synchronization message indicative of the respective slave clock from each of the plurality of slave units at a first validator. The method also includes time-synchronizing a plurality of validator clocks of the first validator to the corresponding plurality of slave clocks using the reverse time-synchronization messages from the plurality of slave units, and validating the time-synchronization between the plurality of slave clocks at the first validator based on the plurality of validator clocks.

Abstract: A system for root cause analysis based on process optimization data is provided. The system receives log data associated with a first trace between a first activity and a second activity of a process. The system further determines a state of inefficiency between the first activity and the second activity based on the received log data. The system further applies a first machine learning (ML) model on the received log data. The system further determines a first label and a first value to be associated with the first trace of the process based on the application of the first ML model. The system further generates presentation data associated with the determined state of inefficiency of the first trace based on the determination of the first label and the first value and further transmits the generated presentation data on a user device.

Abstract: An example embodiment involves rules related to repairing software programs, wherein the rules associate indications of software program failures with repair applications that are configured to correct the software program failures. One or more processors are configured to: (i) receive, by a predictive model, a representation of an execution history of a particular software program, wherein the predictive model has been trained on a corpus of execution histories of the software programs; (ii) generate, by the predictive model and from the execution history, a failure prediction for the particular software program; (iii) receive, by an automated repair controller application, the failure prediction from the predictive model; (iv) based on applying the rules to the failure prediction, determine, by the automated repair controller application, a repair application from the repair applications; and (v) cause, by the automated repair controller application, the repair application to be executed within the network.

Abstract: A method performs time-synchronization between a master clock and a plurality of slave clocks. The method performs a forward time-synchronization from the master clock to the plurality of slave clocks. Further, the method performs a reverse time-synchronization from the plurality of slave clocks to a corresponding plurality of validator clocks. In addition, the method validates the time-synchronization between the plurality of slave clocks, notably between the master clock and the plurality of slave clocks, based on the plurality of validator clocks.