Abstract: A system includes circuitry for rewriting blockchains in a non-tamper-evident or tamper-evident operation by a selected trusted party during a rewrite-permissive phase for the selected trusted party. During a rewrite-embargoed phase for the selected trusted party, rewrite access may pass to at least one second trusted party in a turn-based scheme. In some implementations, rewrite access may be implemented by controlling access to combination of a turn-control key secret portion with respective key secret portions controlled the by the individual trusted parties. Using the access to combination with the turn-control key secret portion, the trusted parties may preform rewrites to the blockchain.

Abstract: A knowledge graph virtualization system (KGVS) implements data virtualization techniques using semantic knowledge when parsing a knowledge graph to return results to a query. The data virtualization using semantic knowledge enable end users and applications to describe desired output without detailed knowledge of underlying data storage, schema, and relationships.

Abstract: A system supports asset transfers among blockchains of differing distributed ledger technologies using interop circuitry. The interop circuitry may receive asset permissions from origin and target participant circuitry. The asset permissions may support transfer of an asset from an origin blockchain to a target blockchain. The interop circuitry, acting on behalf of the origin and target participant circuitry, locks an asset on the origin blockchain. Then the interop circuitry creates the asset on the target blockchain. The locking of the asset on the origin blockchain may prevent a double-expend opportunity, where the asset can be redeemed on the origin blockchain and on the target blockchain.

Abstract: An optimized test data selection strategy references a sampling file that identifies data attributes that serve as the basis of the test data selection strategy. By analyzing fields and the corresponding field values of the sample imprint, a total number of test data selected for inclusion into a sample dataset is reduced. The test data selection strategy provides an efficient methodology for implementing a data comparison testing process.

Abstract: An optimized test data selection strategy references a sampling file that identifies data attributes that serve as the basis of the test data selection strategy. By analyzing fields and the corresponding field values of the sample imprint, a total number of test data selected for inclusion into a sample dataset is reduced. The test data selection strategy provides an efficient methodology for implementing a data comparison testing process.

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: A system may provide hardware acceleration for corrective blockchain-based record entry. Blockchain management circuitry (BMC) may receive a correction to a record entry. The BMC may access a consensus operating procedure. The BMC may apply the consensus operating procedure to the record entry to determine a corrective indicator. After completing the consensus operating procedure, the BMC may append a corrective block generated based on the record entry and corrective indicator to the blockchain. Accordingly, the system may ensure that corrective blocks added to the blockchain were generated in compliance with the consensus operating procedure.

Abstract: Techniques are described for collecting sensor data associated with a wheelchair and, based on the sensor data, determining metric(s) for a user of the wheelchair. Sensor(s) attached to, or in proximity to, the wheelchair may collect sensor data describing the wheelchair and/or its component(s), such as location, velocity, acceleration, direction of movement, orientations (e.g., pitch, yaw, roll), angular velocity of wheels, angular acceleration of wheels, and so forth. The sensor data may be analyzed to determine (e.g., fitness) metrics such as a caloric burn rate, a metabolic burn rate, and/or power expenditure of the user while the user is employing the wheelchair to exercise or otherwise move. The metric(s) and/or sensor data may be presented to the user through a user interface on a smartphone, tablet computer, wearable computer, or other device, to enable the user to monitor fitness metric(s) during use of the wheelchair.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating a database, including identifying a plurality of assets, each asset associated with a database query; parsing the plurality of assets to identify metadata associated with each asset; analyzing the metadata to identify a plurality of enterprise terms; providing, in response to the analyzing, one or more database models, the one or more database models storing relationships between the assets and the metadata, the relationships including, for one or more of the assets of the plurality of assets, a link between the asset and a particular enterprise term of the plurality of enterprise terms that is determined to be associated with the asset; and storing the database models.

Abstract: An application testing developer system provides a platform for generating real-time suggestions for allocating test cases to testers in a distributed environment based on monitored characteristics from previous testing of a test application. The application testing developer system includes a smart advisory tool that optimizes test case allocation in real-time, adaptively assigns incentives in real-time to test cases for prioritizing testing of certain test cases over others, and monitors and validates testing activities.

Abstract: A development platform system is disclosed that provides a development platform configured to create new and modified web-based applications. The development platform may be configured to search for and select a design layout template from available design layout templates stored on a database library. The development platform may further be configured to search for and select a data visualization template from available data visualization templates stored on a database library. The development platform may further be configured to generate a data visualization modification interface and accept a client device customization input to modify attributes of a data visualization. Templates that are modified by the development platform may be stored for subsequent look-up on a database library according to metadata describing attributes of the templates.

Abstract: Data conversion circuitry receives structured records including normalized data and performs a data conversion process on the structured records to generate unstructured records including unstructured syntax. The data conversion circuitry performs the data conversion process according to an unstructured syntax requirement including a syntax field mapping between the structured records and the generated unstructured records.

Abstract: A device may receive information associated with an application to be tested. The device may identify test data associated with the application to be tested based on the received information. The device may associate the test data with a plurality of test cases. The device may associate the plurality of test cases with a test set. The device may associate the test set with a release. The device may provide the plurality of test cases and the test data, associated with the release, to the application to be tested. The device may receive a plurality of first results, and may compare the plurality of first results and a plurality of second results. The device may provide information for display based on comparing the plurality of first results and the plurality of second results.

Abstract: Resource visualization, evaluation, and selection is often a difficult, complex, technically challenging endeavor. This is particularly true when there the resource set is extensive, the resources have widely varying attributes and capabilities, and the resources are also widely disbursed geographically. A multi-dimensional resource evaluation and visualization system implements technical solutions to these technical challenges.

Abstract: Resource visualization, evaluation, and selection is often a difficult, complex, technically challenging endeavor. This is particularly true when there the resource set is extensive, the resources have widely varying attributes and capabilities, and the resources are also widely disbursed geographically. A multi-dimensional resource evaluation and visualization system implements technical solutions to these technical challenges.

Abstract: Implementations include deploying portions of a model used in a cognitive computing process for execution on respective devices in a distributed system, and include processing a device list to provide a benchmark list that includes an inventory of devices across systems that provide data for execution of the model used in the cognitive computing process, each device being a candidate for executing at least a portion of the model, the benchmark list including the devices, and, for each device, accuracies of the device with respect to the at least a portion of the model, providing a deployment plan based on the device and benchmark lists, the deployment plan specifying tasks to be executed by each device, at least two devices included in respective systems, at least one device providing data that is to be processed based on the at least a portion of the model, and executing the deployment plan.

Abstract: In one implementation, a wearable device for providing non-visual guidance to users includes one or more wireless interfaces to obtain information about the wearable device's current surroundings; one or more processors to (i) determine whether to provide non-visual guidance to a user wearing the wearable device based on the information obtained by the one or more wireless interfaces, and (ii) identify particular non-visual guidance to output to the user based on the determination of whether to provide non-visual guidance and the information; a haptic feedback array including a plurality of haptic motors arranged across at least a portion of the wearable device so that each of the plurality of haptic motors, when activated, provides haptic feedback from a distinct location of the wearable device; and a haptic engine to control the haptic feedback array to provide particular patterns of pulses that correspond to the particular non-visual guidance.

Abstract: Methods, systems, and apparatus for training a machine learning model to route received computational tasks in a system including at least one quantum computing resource. In one aspect, a method includes obtaining a first set of data, the first set of data comprising data representing multiple computational tasks previously performed by the system; obtaining input data for the multiple computational tasks previously performed by the system, comprising data representing a type of computing resource the task was routed to; obtaining a second set of data, the second set of data comprising data representing properties associated with using the one or more quantum computing resources to solve the multiple computational tasks; and training the machine learning model to route received data representing a computational task to be performed using the (i) first set of data, (ii) input data, and (iii) second set of data.

Abstract: A crowdsource assistant provides guidance to crowdsource resources navigating a crowdsource platform to bid for and be accepted to accomplish tasks. The crowdsource assistant utilizes machine learning to train similarity computation models that improve the crowdsource assistant's computing capability to generate more relevant recommendations to a resource in a faster and more efficient manner.

Abstract: A device may receive an alarm from a network and determine whether to process the alarm using a robotic process automation (RPA) engine or a machine learning automation (MLA) engine. Based on the determination, the device may selectively cause the alarm to be processed by the RPA engine or the MLA engine. The device may receive data associated with a network performance indicator and may provide the data to the MLA engine. The MLA engine may use a machine learning model to assign a score to the data and may determine whether to generate a trouble ticket based on the score.