Abstract: Methods, systems, and computer-readable storage media for automatic creation of distributed ledger networks. A request to deploy a distributed ledger network is received by an automation framework. The request comprising a configuration file and is associated with a platform type for one or more platforms for deployment of the distributed ledger network. Configuration prerequisites are determined for performing installations of software components on the one or more platforms. In response to installing the software components, the software components are configured and executed to set up an environment for deploying the distributed ledger network by creating a build folder, copying the configuration file and key files for accessing a source code repository into the build folder, and updating the configuration file according to criteria associated with the platform type.

Abstract: A method for detection of a corrupted sensor including providing a first sensor; identifying one or more correlating sensors to the first sensor; determining a correlation between the first sensor and the correlating sensors according to historical sensor values; obtaining a calculated value of the first sensor based on values of the correlating sensors and the correlation; obtaining a measured value of the first sensor; and determining whether the first sensor is corrupted according to a difference between the calculated value and the measured value of the first sensor.

Abstract: In some examples, energy cost reduction of metaverse operations may include generating a unified model of What-IF scenarios. For a semantic association graph of organization avatar entities and for each logically independent IF scenario of a plurality of logically independent IF scenarios of the What-IF scenarios, a sub-metaverse of semantically connected organization avatar entities may be determined. State transitions of the semantically connected organization avatar entities may be iteratively performed until the sub-metaverse reaches a stationarily stable state or an operating limit. A determination may be made as to whether a goal condition is met in the sub-metaverse. For each of the logically independent IF scenarios for which the goal condition is met, an overall energy cost may be determined, and a logically independent IF scenario that includes a minimum energy cost may be identified and used to control an operation for an organization entity.

Abstract: Knowledge graph systems are disclosed for implementing multiple approaches, including stand alone or combined approaches, for knowledge graph pruning. The approaches are based on graph sampling work such as, for example, information gain theory. The approaches are applied by a knowledge graph system to perform schema pruning, automatic graph pruning, and query correlation for improving query performance.

Abstract: A system for predicting the occurrence of an event includes an event detector and a reporting processor. The event detector is configured to: receive data that defines a plurality of social media items; receive a real-time data feed; and predict the occurrence of an event based on a correlation between information in the plurality of social media items and activity associated with the real-time data feed. The reporting processor is configured to determine an event type associated with the event; identify a sentiment of the predicted event based on historical data in the real-time data feed, and generate a recommendation for preventing the occurrence of the event based on at least one of the event type and the sentiment of the predicted event. The recommendation includes a plurality of actions. The reporting processor is coupled to a knowledge graph database that corresponds to an ontology that defines one or more relationships between event types, and response types.

Abstract: An Artificial Intelligence (AI)-based data processing system processes current data to determine if the quality of the current data is adequate to be provided to data consumers and if the quality is adequate, the current data is further analyzed to determine if an impacted load including changes to dimension data of the current data or an incremental load including changes to fact data of the current data is to be provided to the data consumers. Depending on the amount of data to be provided to the data consumers, processing units (PUs) may be determined and assigned to carry out the data upload. Various machine learning (ML) models that are used to provide predictions from the current data are analyzed to determine the quality of predictions and if needed, can be automatically retrained by the data processing system.

Abstract: Embodiments of this disclosure disclose provisioning a cloud service on a vehicle. The method may include, in response to receiving a registration request for cloud services for a vehicle and determining a geographical location of the vehicle based on the registration request. The method may further include identifying cloud services available to the geographical location and extracting capability information of the vehicle from real time series data of the vehicle. The method may further include determining cloud services applicable to the vehicle from the cloud services available to the geographical location based on the extracted capability information of the vehicle and in response to receiving a service subscription request from the vehicle, provisioning on the vehicle a cloud service applicable to the vehicle corresponding to the service subscription request.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for ordering events within a distribution computing system are described. In one aspect, a method includes receiving, by an upward node from one or more nodes of a distributed computing system, event fragments for corresponding events that have occurred within the distributed computing system. Each event fragment includes an age parameter that indicates an age of the corresponding event from a perspective of a node that sent the event fragment to the upward node. The upward node calculates, for each event, a corresponding disentangled time based on a received time that represents a time at which the upward node received the event fragment for the event and the age of the event indicated by the age parameter for the event. The upward node arranges the events in an order according to the disentangled time for each event.

Abstract: Methods, systems and apparatus, including computer programs encoded on computer storage medium, for implementation of secret superposition protocols. In one aspect a method includes, performing, by a sender party, quantum operations on one or more qubits, comprising preparing, according to a predetermined secret superposition protocol, one or more qubits in respective uniform superposition quantum states; transmitting, by the sender party, to a recipient party, and through a secure channel, data indicating use of the predetermined secret superposition protocol; and transmitting, by the sender party and to the recipient party, one or more of the qubits, to wherein the recipient party performs one or more measurements on the qubits to verify use of the predetermined secret superposition protocol.

Abstract: A device may receive, in near-real time, unstructured data associated with an application or a system, and may extract textual data from the unstructured data. The device may parse the textual data to generate parsed textual data, and may perform natural language processing on the parsed textual data to generate processed textual data. The device may process the processed textual data, with a clustering model, to identify topical data associated with the processed textual data, and may process the topical data, with a classification model, to group the topical data into categories. The device may generate a knowledge graph based on the categories, and may store the knowledge graph in a data structure. The knowledge graph may enable the device to provide answers to questions associated with the application or the system.

Abstract: A device may receive activity data identifying activities of a process performed by users via user devices. The device may receive baseline data identifying baselines associated with the process and variant data identifying variants from the baselines. The device may apply a sequence alignment model, to the activity data and the baseline data, to determine first similar sequences associated with the activities and the baselines and may apply the sequence alignment model, to the activity data and the variant data, to determine second similar sequences associated with the activities and the variants. The device may determine, based on the first similar sequences, first label data identifying first labels for the activities and may determine, based on the second similar sequences, second label data identifying second labels for the activities. The device may generate a process diagram based on the activity data, the first label data, and the second label data.

Abstract: Systems, methods, and computer-readable storage media configured to predict future system failures are disclosed. Performance metrics (e.g., key performance indicators (KPIs)) of a system may be monitored and machine learning techniques may utilize a trained model to evaluate the performance metrics and identify trends in the performance metrics indicative of future failures of the monitored system. The predicted future failures may be identified based on combinations of different performance metrics and the impact that the performance metric trends of the group of different performance metrics will have on the system in the future. Upon predicting that a system failure will occur, operations to mitigate the failure may be initiated. The disclosed embodiments may improve overall performance of monitored systems by: increasing system uptimes (i.e.

Abstract: This disclosure relates generally to ASR and is particularly directed to automatic, efficient, and intelligent detection of transcription bias in ASR models. Contrary to a tradition approach to the testing of ASR bias, the example implementations disclosed herein do not require actual test speeches and corresponding ground-truth texts. Instead, test speeches may be machine-generated from a pre-constructed reference textual passage according short speech samples of speakers using a neural voice cloning technology. The reference passage may be constructed according to a particular target domain of the ASR model being tested. Bias of the ASR model in various aspects may be identified by analyzing transcribed text from the machine-generated speeches and the reference textual passage. The underlying principles for bias detection may be applied to evaluation of general transcription effectiveness and accuracy of the ASR model.

Abstract: Systems and methods for managing supply chain of products and services are disclosed herein. A system generates supply chain data based on historical data received from data sources corresponding to supply chain of product or service. Further, system extracts data entity and set of attributes from supply chain data, to determine semantically related data entities. Furthermore, system determines use case corresponding to management of supply chain, based on semantically related data entities. Additionally, system predicts, risk or priority associated with product or service in the supply chain, to generate risks and alerts, based on prediction. Further, system assigns critical and high-priority use case to one or more agents based on a performance score of the one or more agents. Furthermore, system provides insights and suggestions for managing the supply chain of product or service at regional level and global level of supply chain.

Abstract: This document described pressure-sensitive human machine interface (HMI) devices. In some aspects, a pressure-sensitive human-machine interface (HMI) device may include a surface element comprising an outer surface for receiving pressure inputs. The HMI device may also include multiple pressure-sensitive input regions that each include one or more positive electrodes and one or more return electrodes. The HMI device may also include a pressure-sensitive conductive sheet disposed adjacent to or between the one or more positive electrodes and one or more return electrodes of the multiple pressure-sensitive input regions.

Abstract: Implementations of the present disclosure include providing a graph representative of a network, a set of nodes representing respective assets, each edge representing one or more lateral paths between assets, the graph data including configurations affecting at least one impact that has an effect on an asset, determining multiple sets of fixes for configurations, each fix having a cost associated therewith, incorporating fix data of the sets of fixes into the graph, defining a set of fixes including one or more fixes from the multiple sets of fixes by defining an optimization problem that identifies one or more impacts that are to be nullified and executing resolving the optimization problem to define the set of fixes, each fix in the set of fixes being associated with a respective configuration in the graph, and scheduling performance of each fix in the set of fixes based on one or more operational constraints.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for dynamic user data filtering. In some implementations, a method includes determining one or more values using data representing a sequence of one or more types of interactions between a user and content; using the one or more values to determine whether to include each interaction of the one or more types of interactions in the sequence within a reduced user data set; generating the reduced user data set by removing one or more interactions from the sequence based on determining not to include the one or more interactions using the one or more values; and providing the reduced user data set to a processing server.

Abstract: Systems and methods for deep technology innovation management by cross-pollinating innovations dataset are disclosed. A system extracts context-based keyword from an innovation dataset by transforming the innovation dataset to a vector. Further, the system searches semantically relevant keywords for the extracted context-based keyword, by extracting an entity and a key phrase from the extracted a context-based keyword. Furthermore, system clusters the vector, by identifying frequent keywords in the semantically relevant keywords to obtain cluster centroids of the frequent keywords. Thereafter, the system determines weighted keywords in each cluster using the obtained cluster centroids, and classifies the weighted keywords to identify emerging innovation trends relevant to the innovation in the innovation dataset. The system forms cohorts of innovators to explore the reuse of innovations, assets, code, and build focused monetization model.

Abstract: In some implementations, a device may receive, from a user device, a query for information from a user. The device may receive, from an enterprise system, data identifying products and services to be offered by the user. The device may process the query and the data, with a model, to identify a subject of the query and a context for the subject. The device may process the subject and the context, with a model, to determine a workflow for the user. The device may process the data, the subject of the query, and the context for the subject, with a model, to determine a key performance indicator or a decision associated with one of the products or the services. The device may provide information identifying the workflow, the key performance indicator, and/or the decision to the user device via a virtual assistant or a user interface.

Abstract: The validity of engineering drawings is automatically determined based on compliance of the specifications of the engineering drawings with automatically generated rules. A document package including images of the engineering drawings and related documents is received. Rules codifying the requirements to be fulfilled by the engineering drawings are automatically generated from the related documents. Data such as specifications of the various parts of the entities in the engineering drawings are automatically extracted. The extracted data is analyzed to determine compliance with the rules to validate the engineering drawings.