Abstract: A method may include accessing, from a data store, telemetry data for an application, the telemetry data identifying actions executed by the application for a set of users of the application; retrieving an engagement index for the application using the telemetry data based on an engagement index profile, the engagement index profile identifying a selection of actions and a set of calculation dimensions; and presenting a user interface, the user interface including: a first portion identifying the selection of actions; a second portion identifying the set of calculation dimensions; a third portion identifying an original value of an action of the selection of actions with respect to a dimension in the set of calculation dimensions; and a fourth portion identifying a weighted composite value of the action with respect to set of calculation dimensions.

Abstract: A method may include accessing, from a data store, telemetry data for an application, the telemetry data identifying actions executed by the application for a set of users of the application; retrieving an engagement index for the application using the telemetry data based on an engagement index profile, the engagement index profile identifying a selection of actions and a set of calculation dimensions; and presenting a user interface, the user interface including: a first portion identifying the selection of actions; a second portion identifying the set of calculation dimensions; a third portion identifying an original value of an action of the selection of actions with respect to a dimension in the set of calculation dimensions; and a fourth portion identifying a weighted composite value of the action with respect to set of calculation dimensions.

Abstract: Non-limiting examples of systems, methods, and devices for automatic triaging of diagnostic failures for heterogeneous groups of tenants of a Software-as-a-Service, multi-tenant environment are disclosed herein. In an implementation, telemetry data for the heterogeneous groups of tenants is analyzed to classify individual tenant failures and detect the health status of the individual tenant. Tenant failures and/or tenant health statuses are filtered according to a threshold level. Anomalies having metrics that meet or exceed the threshold level are further analyzed to determine their priority (e.g., to a specific tenant). If the anomalies are known, then an existing entry for the anomaly is tagged and its priority may be changed. If the anomalies are unknown, then an entry is generated for the anomaly and prioritized. Tenants may be notified of a detected anomaly and may provide feedback. The feedback may be used to update triaging models.

Abstract: Systems and methods for evaluation of entity health for a product are described. In some embodiments, a computing system can receive data defining values of a group of diagnostic signals pertaining to a domain of a product of an entity. The computing system can then generate attributes indicative of entity health condition in the domain by applying a machine-learning model to the data. The attributes can include a health reward parameter and a signal strength parameter. The computing system also can encode the health reward parameter in a particular marking according to a marking schema. The computing system can further cause presentation of the particular marking and/or the signal strength parameter.

Abstract: A smart rollout recommendation system uses a modernization score that indicates a likelihood of accepting a change in an existing product to identify at least one tenant of a plurality of tenants eligible to receive the change and the timing of the rollout. The modernization score is generated using a set of attributes extracted from tenant profiles and a machine learning model.

Abstract: Non-limiting examples of systems, methods, and devices for automatic triaging of diagnostic failures for heterogeneous groups of tenants of a Software-as-a-Service, multi-tenant environment are disclosed herein. In an implementation, telemetry data for the heterogeneous groups of tenants is analyzed to classify individual tenant failures and detect the health status of the individual tenant. Tenant failures and/or tenant health statuses are filtered according to a threshold level. Anomalies having metrics that meet or exceed the threshold level are further analyzed to determine their priority (e.g., to a specific tenant). If the anomalies are known, then an existing entry for the anomaly is tagged and its priority may be changed. If the anomalies are unknown, then an entry is generated for the anomaly and prioritized. Tenants may be notified of a detected anomaly and may provide feedback. The feedback may be used to update triaging models.

Abstract: A method of and system for performing pilot testing of a software program in an organization is carried out by collecting pilot testing data generated from a pilot testing of a software program run on one or more hardware assets in the organization, determining whether a sufficient amount of pilot testing data has been collected, and, when so, calculating one or more pilot test metrics from the collected data. The calculated pilot test metrics may then be compared to similar metrics in a target population to evaluate the software program.

Abstract: A system is disclosed, which includes a processor and a memory in communication with the processor. The memory includes executable instructions that, when executed by the processor, cause the processor to control the system to perform functions of collecting software asset information of software assets installed in hardware assets of an organization; determining popularity metrics of the software assets based on the collected software asset information; classifying, based on the popularity metrics, the software assets into a plurality of popularity groups; identifying, based on the classification, a pilot test software asset sample group; identifying, based on the pilot test software asset sample group, a pilot test hardware asset sample group; and deploying the new software asset to the pilot test hardware asset sample group for executing the pilot test of the new software asset.

Abstract: In one example, a system includes an electronic processor configured to receive telemetry data originating from a plurality of client applications. The telemetry data includes data points associated with errors associated with one or more operations. The electronic processor also classifies the telemetry data based a plurality of classes of data, converts the plurality of classes of data into one or more metrics based on a plurality of dimensions, and aggregates the metrics for the classes of data by all the dimensions. The electronic processor accesses a predictive scoring model for a stored metric associated with a dimension of interest, determines a prediction error associated with the dimension of interest, detects an anomaly based on an item selected from the group consisting of the prediction error and a static threshold, and transmits an alert message, generates a bug report, and stores the bug report in a database.

Abstract: Disclosed are methods and devices to provide efficient methods and systems for discovering therapeutic targets, novel antigens, and for deciphering an immunosignature. The invention discloses methods for the identification of unique peptides which form an immunosignature. The invention can be applied to target identifying screening in drug discovery.

Abstract: A method of and system for performing pilot testing of a software program in an organization is carried out by collecting pilot testing data generated from a pilot testing of a software program run on one or more hardware assets in the organization, determining whether a sufficient amount of pilot testing data has been collected, and, when so, calculating one or more pilot test metrics from the collected data. The calculated pilot test metrics may then be compared to similar metrics in a target population to evaluate the software program.

Abstract: A system is disclosed, which includes a processor and a memory in communication with the processor. The memory includes executable instructions that, when executed by the processor, cause the processor to control the system to perform functions of receiving software asset information of a plurality of software assets installed in a plurality of hardware assets of an organization; determining popularity metrics of the software assets based on the collected software asset information; classifying, based on the popularity metrics, the software assets into a plurality of popularity groups; identifying, based on the classification, a group of the software assets to be validated for a software update; identifying, based on the identified group of the software assets, a group of the hardware assets to be tested for the software update; and deploying the software update to the identified group of the hardware assets to validate the identified group of the software assets.

Abstract: A system for scoring route safety includes and input interface and a processor. The input interface is to receive data associated with a route segment. The data includes a speed data. The processor is to determine a segment safety score using a speed distribution. The speed distribution is based at least in part on the speed data.

Abstract: A system for scoring route safety includes and input interface and a processor. The input interface is to receive data associated with a route segment. The data includes a speed data. The processor is to determine a segment safety score using a speed distribution. The speed distribution is based at least in part on the speed data.

Abstract: A device including a processor and memory is disclosed. The memory includes executable instructions that cause the processor to control the device to perform functions of identifying a pool of assets to be covered by a pilot test; receiving attributes associated with the identified assets in the pool; identifying a set of pilot test parameters associated with the pilot test; comparing the attributes of the assets with the identified set of pilot test parameters associated with the pilot test; based on a result of the comparison, providing a unique ranked order of the identified assets in the pool and selecting an asset from the unique ranked order to be placed in a pilot test group. When a stop condition is not satisfied, a footprint of the asset placed in the pilot test group is removed from the pool and the set of pilot test parameters.

Abstract: In one example, a system includes an electronic processor configured to receive telemetry data originating from a plurality of client applications. The telemetry data includes data points associated with errors associated with one or more operations. The electronic processor also classifies the telemetry data based a plurality of classes of data, converts the plurality of classes of data into one or more metrics based on a plurality of dimensions, and aggregates the metrics for the classes of data by all the dimensions. The electronic processor accesses a predictive scoring model for a stored metric associated with a dimension of interest, determines a prediction error associated with the dimension of interest, detects an anomaly based on an item selected from the group consisting of the prediction error and a static threshold, and transmits an alert message, generates a bug report, and stores the bug report in a database.

Abstract: A system for determining a driver fuel score an input interface and a processor. The input interface is to receive a fuel efficiency measure for a vehicle or a vehicle type for a plurality of drivers. The processor is to determine a relative fuel performance score based at least in part on the relative fuel performance and determine a driver performance score based at least in part on the relative fuel performance.

Abstract: Disclosed are methods and devices to provide efficient methods and systems for discovering therapeutic targets, novel antigens, and for deciphering an immunosignature. The invention discloses methods for the identification of unique peptides which form an immunosignature. The invention can be applied to target identifying screening in drug discovery.