Abstract: A device may receive information that identifies code associated with an application. The device may generate a technical description of the code based on the information that identifies the code associated with the application. The device may generate a set of rules based on the technical description of the code. The set of rules being associated with a semantics of business vocabulary and business rules (SBVR) format. The device may generate a set of microservices based on the set of rules. The device may provide information that identifies the set of microservices to cause an action to be performed.

Abstract: A device obtains a machine readable document, and extracts plain text information from the machine readable document. The device extracts visual structural information from the machine readable document, and processes the plain text information with an artificial intelligence model to generate artificial intelligence-generated annotations. The device aligns the artificial intelligence-generated annotations and the visual structural information to generate a structured document, and provides the structured document for display.

Abstract: Systems and methods for predictively responding to real-time sensor data from an computer-augmented environment are provided. A system may receive sensor data from the computer-augmented environment. The system may obtain a feature model, a prediction model, and a filter criteria. The system may derive, based on the feature model and the sensor data, a first event. The system may determine the first event is associated with an authorized event identifier in the filter criteria. The system may forecast, based on the authorized event identifier and the prediction model that a second event occurs after the first event. The system may transmit an action message to the computer-augmented environment, the action message indicative of the second event. Updates to the feature model, the prediction model, and/or the filter criteria may occur in batch using machine learning and statistical analytics while the real-time platform predictively responds to the sensor data.

Abstract: Examples of automated order troubleshooting are described. In an example embodiment, sales-specific data sources associated with at least one of a process, an organization, and an industry relevant for sales operations are monitored. From the monitored sales-specific data, an operation behavioral pattern is identified, based on predefined rules. Subsequently, a behavior model capturing the operation behavioral pattern is constructed using a pre-existing behavior model library. Using the behavior model, a potential event relating to an order received to be fulfilled using the sales operation is predicted, the potential event being indicative of an issue affecting the order. Accordingly, the issue affecting the order is proactively remediated to automatically troubleshoot the order.

Abstract: A system includes circuitry for rewriting blockchains in a non-tamper-evident or tamper-evident operation using a key secret held in portions by multiple individually untrusted parties. The blockchains may include a series of blocks secured by integrity codes that may prevent non-tamper-evident rewrites by non-trusted parties that are not in possession of the key secret or individually-untrusted parties in possession of only a portion of the key secret. In some cases, multiple individually-untrusted parties may combine their portions into the key secret. As a group, the multiple individually-untrusted parties may perform non-tamper-evident operation with respect to at least one integrity code within the blockchain.

Abstract: A device may receive sensor data from one or more sensor devices. The device may detect a trigger condition, that triggers an update to a model used to analyze the sensor data, based on receiving the sensor data. The trigger condition may include at least one of: a change in a type of data included in the sensor data, a change in an entity being monitored in association with the sensor data, or a change in a frequency with which the sensor data is received from the one or more sensor devices. The device may transmit a request to update the model based on detecting the trigger condition. The device may receive an updated model based on transmitting the request to update the model. The device may apply the updated model to the sensor data and/or subsequent sensor data received from the one or more sensor devices.

Abstract: A multi-layer resource control stack based system may generate an availability indication for multiple domains supported by the resource control stack and send the indication to a client node. The client node may respond with a selection of a domain. The client node may also indicate a compute resource to be managed by the resource control stack. In response to the selection from the client node, the resource control stack may initiate a virtual representation of the domain. The client node may interact with the virtual representation to receive recommendations, utilization data, and control information relevant to the compute resource and within a subject area associated with the domain.

Abstract: A method and systems for developing a composite sequence for electrical power transmission and distribution equipment in a power system are provided. The system includes a sequencing generation circuitry to generate a composite sequence for electrical power transmission and distribution equipment according to a demographics sub-sequence, a utilization sub-sequence, a maintenance sub-sequence, a performance sub-sequence, a criticality sub-sequence and a condition sub-sequence. The system also includes a first sub-model to predict a future equipment sequence of the electrical power transmission and distribution equipment in the power system and a second sub-model that generates the replacement control scheme for replacing utilities assets.

Abstract: Methods, systems, and apparatuses, including computer programs encoded on a computer storage medium, for monitoring a condition of an appliance.

Abstract: A first device may receive connection requests to establish communications between a second device located behind a firewall and a third device located outside of the firewall. The first device may be located outside of the firewall. The second device and the third device may store data. The first device may receive a request for the data. The first device may provide the request via a first connection or a second connection. The device may receive the data. The data stored by the second device may be received by the first device from behind the firewall without using a tunnel through the firewall and in a streaming manner. The first device may provide the data. The data stored by the third device may be provided to the second device in the streaming manner.

Abstract: Systems and methods for remediating errors in distributed computing are provided. A system may include a remediation node. The remediation node may forecast receipt of a service request by a service authority. The service request may be configured to cause the service authority to modify a service assigned to an account. The service authority may be in communication with a plurality of source systems. The remediation node may acquire, from at least one of the source systems, a service parameter in which the service authority is configured to access to process the service request. The remediation node may determine an error condition corresponding to the service parameter. The remediation node may communicate, in response to determination of error condition, a remediation instruction to the at least one of the source systems, the remediation instruction configured to cause the at least one of the source systems to modify the service parameter.

Abstract: Knowledge graph systems are disclosed for enhancing a knowledge graph by generating a new node. The knowledge graph system converts a knowledge graph into an embedding space, and selects a region of interest from within the embedding space. The knowledge graph system further identifies, from the region of interest, one or more gap regions, and calculates a center for each gap region. A node is generated for each gap region, and the information represented by the node is added to the original knowledge graph to generate an updated knowledge graph.

Abstract: A device may obtain, from one or more cameras, an image that depicts one or more encoded decals positioned on a body of a vehicle. The device may process the image and may identify, based on processing the image, one or more characteristics of the one or more encoded decals. The device may determine, based on the one or more characteristics of the one or more encoded decals, positioning information to be used to position a loading bridge relative to the body of the vehicle. The device may determine one or more control signals based on the positioning information. The device may provide the one or more control signals to one or more actuators to automatically position the loading bridge relative to the body of the vehicle.

Abstract: Implementations are directed to integrating a computer-executed service platform with multiple channels, and include actions of providing a transition layer as an application executed on a client-side device, which receives input from a channel of the multiple channels, and providing a unified input that is in a unified format for processing by the service platform, receiving, by the service platform, the unified input, identifying, by the service platform, a set of actions based on the unified input, the set of actions including to be executed by one or more back-end services, providing a service layer including a plurality of bots, each bot interacting with a back-end service based on an action to receive at least one result from the respective back-end service, receiving result data including data describing the at least one result, and transmitting an output based on the result data through the transition layer of the client-side device.

Abstract: A machine provides a system and interface to allow domain experts and other users to develop, deploy, and iterate on analytical models. The machine facilitates building, deploying, and/or training analytical models by, e.g., exposing analytical model configuration parameters to a user while abstracting model building and model deployment activities. The machine can also determine resource loads or execution times for various analytical models and can schedule model execution accordingly. The machine also provides a dynamically reconfigurable user interface for controlling the system.

Abstract: A first device may receive, from a second device, an input corresponding to a search for an item, may identify a set of items, and may determine a set of trend scores associated with the set of items. The first device may determine a set of sentiment scores, and may identify a subset of items, of the set of items, based on the set of trend scores and the set of sentiment scores. The first device may provide, to the second device, information associated with the subset of items to permit the second device to provide, for display, the information associated with the subset of items, and may receive, from the second device, information associated with a selected item, of the subset of items. The first device may determine a return score associated with the selected item, and may perform an action based on the return score.

Abstract: A device may communicate with a group of devices to obtain data regarding a set of events occurring for the group of devices. The device may process the data regarding the set of events to remove a subset of data entries, from the data, that is associated with an anomalous event. A first layer of analysis may relate to the group of devices, a second layer of analysis relating to a set of sessions of operating a user interface via the group of devices, and a third layer of analysis relating to information provided via the user interface. The device may perform the multiple layers of analysis via a machine learning technique to identify an alteration relating to the information provided via the user interface. The device may alter the information provided via the user interface based on performing the multiple layers of analysis.

Abstract: In the pharmaceutical research and development process, it may be necessary to process large amounts of medical records or clinical literature, to ensure safety of patients consuming a drug. A pharmacovigilance system may assist in this process by efficiently and automatically processing medical records to extract information and relationships contained therein and may also form a preliminary assessment regarding a medical or clinical judgment. The pharmacovigilance system may automatically generate reports based on this information, which may be validated by trained clinicians and medical experts.

Abstract: A knowledge data management system (KDMS) implements data refinement orchestration, resolution, and refinement to provide a reusable and generic solution to ingest and link data via relationships and properties when constructing a knowledge graph. The KDMS thus operates to break down existing data storage silos by normalizing and integrating data with a uniform semantic schema, which results in more accurate and faster knowledge graph construction.

Abstract: A device may receive, from a user device, an implicit search request identifying a resource accessed by a user of the user device. Based on properties defined in a user role and a rule identified in context configuration information, the device may determine an intent associated with the user and a context associated with the intent and the resource accessed by the user. The device may send, based on query options identified in search configuration information, a search query identifying search criteria associated with the context, and may receive a search response identifying available resources that satisfy the search criteria. The device may determine a probability, for each of the available resources, that the available resource matches the context, identify a portion of the search response based on the probabilities, and send the portion to the user device.