Abstract: A device may receive data related to operations of a plurality of managed devices. The device may determine, after receiving the data, a multi-entity profile for the data. The device may determine, using the multi-entity profile, a set of sub-models for the data after determining the multi-entity profile. The set of sub-models may be associated with processing the data in a contextualized manner. The device may generate a model based on the set of sub-models. The device may perform one or more actions related to the plurality of managed devices or the at least one alert based on respective scores associated with the plurality of managed devices after generating the model.

Abstract: An intelligent product requirement configurator is a tool for assisting the implementation process of application platforms by generating a recommended configuration data set describing recommended configuration settings for a selected application platform. The tool acts as a repository for capturing requirements such as banking market practice requirements, regulatory requirements, and bank specific requirements. The tool further converts the requirements into profile data and business rules that are used to configure the application platform.

Abstract: A data archive constructed from source data, whose structure and associated schemas can evolve based on the generated responses to user data requests. Based on the analysis of the responses, the schema and/or archive structure can be modified to provide greater knowledge, definition and operations available to be performed on the data, as well as to reduce the processing and storage costs associated with housing and accessing the data within the archive.

Abstract: A system may receive an item identifier and a container identifier, the item identifier being, for example, encoded in a RFID tag affixed to a physical item and the container identifier being, for example, encoded in an RFID tag affixed to a container. The system may identify, on a blockchain, an item smart contract based on the item identifier and a container smart contract based on the container identifier. The item smart contract may include environmental compliance criteria for the physical item. The system may store, on the blockchain, a mapping between an item smart contract and the container smart contract. The system may receive environmental status information derived from sensor data generated by a sensor affixed to or in the container. The system may determine the environmental status information of the container does not satisfy the environmental compliance criteria included in the item smart contract.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for storing facial recognition image data in a cache. One of the methods includes receiving an image from a camera, detecting, in the received image, a face of a person, searching a biometric data cache based on the detected face, in response to searching the biometric data cache based on the detected face, determining whether the biometric data cache includes data for the person, in response to a determination that the biometric data cache includes data for the person, using the data from the biometric data cache to determine an identifier for the person, and in response to a determination that the biometric data cache does not include data for the person: searching a data storage system based on the detected face of the person to determine whether the data storage system includes data for the person.

Abstract: Methods and systems including computer programs encoded on a computer storage medium, for interactive content recommendation. In one aspect, a method includes receiving a request for content by a user, determining a user intent based on the received request, providing to the user a first attribute responsive to the user intent, receiving a first attribute value responsive to the first attribute, providing a second attribute, and receiving a second attribute value responsive to the second attribute. A particular content vector including a first content attribute and a second content attribute for a particular content item is identified where the first content attribute and the second content attribute sufficiently match the first attribute value and the second attribute value. The particular content item is provided as a suggested content item, and, responsive to a user selection of the particular content item, provided for presentation on the user device.

Abstract: A device may generate, based on receiving feeder content, a structured format of the feeder content. The device may generate, based on the structured format of the feeder content, one or more semantic mappings for the feeder content. The device may generate, based on the one or more semantic mappings for the feeder content, an electronic storyboard of the feeder content. The device may generate an extended reality rendered content feed based on the electronic storyboard of the feeder content. The device may provide the extended reality rendered content feed to an extended reality device.

Abstract: A device creates tasks to implement a software code change in a software code and to generate new software code, and performs, via a development environment, a unit test on the new software code to generate a unit test result. The device performs, via the development environment, a functional test on the new software code to generate a functional test result, and updates, based on the unit test result and the functional test result, the new software code to generate updated new software code. The device performs, via a quality assurance environment, a regression test on the updated new software code to generate a regression test result, and updates, based on the regression test result, the updated new software code to generate final software code. The device automatically deploys the final software code in a production environment, and performs actions based on deploying the final software code.

Abstract: Increases in global population have led to unprecedented challenges in meeting every day needs. Vehicle parking is one such challenge given the limited parking spaces available at any destination, whether at work, at a shopping center, or any other location. A parking resource analysis system includes a stepwise simulator system and a role based access system. The stepwise simulator system tests, simulates, and tunes specific models for issuing parking control actions with respect to a specific lot. The role based access system may be physically located at the parking lot. The role based access system implements dynamic loading or dynamic access of role specific models for issuing parking control actions tailored to the role of the particular individual searching for a parking space.

Abstract: A device receives, as part of a gesture translation service, data that depicts gestures, wherein the data is image data or multimedia data. The device converts a set of frames that include the data to another set of frames that include modified data identifying a grayscale or black and white depiction of the gestures and generates graphical representations of the gestures identified by the modified data. The device selects, using a matching technique, a graphical representation of corresponding gestures that matches or satisfies a threshold level of similarity with the graphical representations of the gestures identified by the modified data. The device identifies response data that is representative of the corresponding gestures based on the response data being stored in association with an identifier of the graphical representation that has been selected. The device provides the response data to be displayed, via an interface, as text data or audio data.

Abstract: A system for determining adverse effects associated with a substance includes a side-effect recognizer, a relationship extractor, a processor, and a reporting system. The side-effect recognizer utilizes a first recurrent neural network (RNN) to identify a first portion of received data associated with an adverse effect to thereby determine the adverse effect associated with the received data. The relationship extractor utilizes a second RNN to identify a second portion of the received data associated with a substance and a third portion of the received data that indicates a relationship between the substance and the adverse effect to thereby determine the substance associated with the received data and the relationship between the substance and the adverse effect. The processor is in communication with the adverse effect recognizer and the substance relationship extractor and aggregates and relates the adverse effect, substance, and relationship.

Abstract: A device may receive, from a user device, a request for a code assessment of a proposed change to an enterprise resource planning (ERP) system of an organization to identify an impact of implementing the proposed change on custom code associated with the ERP system. The device may obtain data identifying custom items associated with the custom code from a data structure associated with the ERP system. The device may generate custom code metadata for the custom items by performing error checks to determine whether the custom items will cause errors after the proposed change is implemented. The device may generate an assessment report for the code assessment by processing the custom code metadata. The device may provide the assessment report for display on an interface of the user device, and may perform actions to permit the proposed change to be implemented without the errors occurring.

Abstract: A cloud migration tool manages and monitors a cloud migration project that migrates data from a legacy environment to a target data center environment. The cloud migration tool includes an analytics engine that applies data regression models to generate a delay risk prediction for activities that are scheduled during the cloud migration project.

Abstract: A device obtains data, for a current media plan, that includes a cost adjustment factor, a duration of an unexecuted portion of the current media plan that is divisible into periods of time, and an unutilized budget, for the duration, that is divisible into budget portions based on the periods of time. The device generates a predictive baseline cost parameter by adjusting, by the cost adjustment factor, a baseline cost parameter of a previously implemented baseline media plan. The device predicts cost metrics for the current media plan using the predictive baseline cost parameter, and predicts performance metrics for the current media plan based on the cost metrics and predictive baseline cost parameter. The device determines target cost per point (CPP) values for the current media plan based on the cost metrics and performance metrics, and causes an action to be performed based on the target CPP values.

Abstract: A multi-layer rate sizing stack may generate prescriptive operation-rate tokens for controlling sizing adjustments for operation-rates. The input layer of the rate sizing stack may generate operation pattern data based on operation-rate data received via network connection. A prescriptive engine layer may determine a prescriptive allowed operation-rate based on the operation pattern data. Based on the prescriptive allowed operation-rate, the prescriptive engine layer may generate the operation-rate tokens that that may be used to control rate sizing adjustments prescriptively.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining retraining predictive models. One of the methods includes maintaining, by a computer system of an enterprise, one or more predictive models. The computer system receives operational data and uses each of the one or more predictive models to generate predictions using the received operational data. An indication of a systemic change in the computer system is received. The method includes determining that one or more retraining rules specify that at least one of the one or more predictive models should be retrained due to the systemic change, and in response, obtaining updated training data and retraining the predictive model using the updated training data.

Abstract: The global proliferation of high speed communication networks has created unprecedented opportunities for geographically distributed resource interaction. However, while the opportunities exist and continue to grow, the realization of those opportunities has fallen behind. A dynamic process execution architecture solves the enormous technical challenges of providing effective and efficient process execution environments for geographically distributed resources to execute a complex project.

Abstract: A device intelligence architecture configures and controls on-site devices and performs environment monitoring to facilitate effective device functionality. The architecture facilitates efficient use of devices (e.g., robotics) in an unstructured and dynamic environment, which will allow deployments in many more environments than is currently possible. The architecture stores and shares information between segregated devices to avoid the silo effect of vendor specific stacks. The architecture also models capabilities of devices and maps actions to intelligence packages to deploy a specific intelligence package to the device. The architecture also implements distributed processing. For instance, computationally intensive tasks may be offloaded to the back end processing, with action updates resulting from the processing pushed to the devices.

Abstract: A system receives sensor data from sensing parameters of a piece of factory equipment. The system includes a first model to generate predicted degradation states of the piece of factory equipment by being trained to generate a stochastic degradation model for classification of the predicted degradation states of a particular asset. The system includes a second model to which the predicted degradation states are provided. The second model trained to generate a covariate indicative of a failure condition of the piece of factory equipment. The system may supply the covariate to the first model to generate predicted degradation states compensated with the covariate. From the predicted degradation states compensated with the covariate a policy of a maintenance action may be generated with the system to optimize life expectancy of the piece of factory equipment. The system may adjust operation of the piece of factory equipment based on the maintenance action.

Abstract: Systems, apparatuses, and methods directed to security enhancement. One or more remote data sources may be accessed to retrieve remote data associated with security for a computing architecture. An input model of an input network security architecture may be identified. One or more user-based constraints may be identified. An output model may be automatically generated based on the input model, the remote data and the one or more user-based constraints. The output model is an output network security architecture that complies with the one or more user-based constraints.