Abstract: Ghost routing is a network verification technique that uses a portion of a production network itself to verify the impact of potential network changes. Ghost routing logically partitions the production network into a main network and a ghost network. The main network handles live traffic while the ghost network handles traffic generated for diagnostic purposes. The ghost network may have a network topology identical to the production network and may use the same hardware and software as the production network. An operator may implement a network configuration change on the ghost network and then use verification tools to verify that the network configuration change on the ghost network does not result in bugs. Verifying on the ghost network may not affect the main network. If the network operator verifies the network configuration change on the ghost network, the network operator may implement the network configuration change on the main network.

Abstract: A method generates data analysis templates. A computing device receives, via a graphical user interface, a natural language input, which includes multiple terms. The terms include one or more data fields and/or data values from a data source. The device designates the natural language input as trigger text for a data analysis template. The trigger text includes the multiple terms. A user defines one or more rules for a subset of the terms, each rule specifying respective criteria to match a respective term in the subset. A user specifies multiple data visualizations corresponding to the trigger text. Each of the data visualizations (i) uses a respective one or more data fields, from the data source, corresponding to terms from the trigger text and (ii) has a respective data visualization type. The device generates the data analysis template according to the trigger text, the user definition, and the user specification.

Abstract: A computer system obtains a data model encoding a first data source as a set of logical tables. The computer system determines, for each data field of a first plurality of data fields included in a first logical table, a respective semantic role for the respective data field using a trained predictive model and according to a first concept corresponding to the first logical table. The computer system displays, in a user interface, a plurality of semantic roles for the first plurality of data fields. The computer system detects, via the user interface, a user input selecting a preferred semantic role for a first data field of the first plurality of data fields. The computer system assigns the preferred semantic role to the first data field and updates the first logical table according to the preferred semantic role that is assigned to the first data field.

Abstract: A computer system receives a user input to specify a natural language command. The computer system, in response to receiving the user input, generates a semantic interpretation for the natural language command using a trained word model, based on semantic annotations for a published data source. The trained word model is trained to identify similar words based on a plurality of processed representations corresponding to a set of words of a natural language. The computer system queries the published data source based on the semantic interpretation, thereby retrieving a dataset, and generates and displays a data visualization based on the retrieved dataset.

Abstract: Systems and methods are disclosed for integrating with third-party applications. An extension module operates with a user interface application on a client computing device. The extension module enables integration of functionality of an associated middleware system. The extension module extracts data from a user interface of a third-party application system based on a regular expression template. The extension module transmits data to the middleware system and receives information from the middleware system. The extension module can alter at least a portion of the user interface based on the information received from the middleware system.

Abstract: A method of measuring temperature of a battery includes attaching at least one sensor holder to a first electrode or a second electrode of a battery, providing at least one temperature sensor placed on the at least one sensor holder, the outer surface of the at least one temperature sensor being flush with the remaining surface of the at least one sensor holder, and wherein the at least one temperature sensor has no contact with a polymer porous separator of the battery, coupling the at least one temperature sensor to a header, wherein the header has a plurality of pins on the outside surface of the housing, connecting a reader to the plurality of pins of the header, and measuring the temperature of the batter.

Abstract: A computing system and method for mapping a migration to a new distributed file system is provided. A method may include receiving file system metadata from an existing distributed file system, comparing permissions for each file and each user, generating a plurality of recommended groups, recommended folders, and recommended permissions, and presenting the recommended groups, recommended folders, and recommended permissions to a user.

Abstract: A computing device receives, in a graphical user interface, a first natural language input directed to a first data source. The device parses the first natural language input and identifies one or more keywords from the input. The device identifies, using the keywords, a plurality of triggers for generating a respective plurality of data visualizations for the first data source. The device determines that the keywords in the first natural language input match a first data field or a first data value in a predefined set of data fields or a predefined set data values constrained by one or more variable terms specified via user configuration input. The computing device identifies a first trigger that is associated with a first plurality of data visualizations. The device generates the first plurality of data visualizations and displays a first data dashboard that includes the first plurality of data visualizations.

Abstract: Examples provide a brake pedal assembly including a pedal housing, a bracket for securement within a vehicle, and a pedal arm having a proximal portion pivotally supported by the pedal housing and a distal portion including a foot pad spaced from the bracket. The pedal arm pivots from an unactuated position to a fully actuated position in response to application of a force to the foot pad. A pedal emulator system provides variable operator feedback as the pedal arm pivots in response to the application of force. The pedal emulator system includes a first spring set engaged with the pedal arm at the unactuated position and operable to bias the pedal arm toward the unactuated position, and a second spring set engaged with the pedal arm only after the pedal arm pivots from the unactuated position to a first intercept position between the unactuated and fully actuated positions.

Abstract: Ghost routing is a network verification technique that uses a portion of a production network itself to verify the impact of potential network changes. Ghost routing logically partitions the production network into a main network and a ghost network. The main network handles live traffic while the ghost network handles traffic generated for diagnostic purposes. The ghost network may have a network topology identical to the production network and may use the same hardware and software as the production network. An operator may implement a network configuration change on the ghost network and then use verification tools to verify that the network configuration change on the ghost network does not result in bugs. Verifying on the ghost network may not affect the main network. If the network operator verifies the network configuration change on the ghost network, the network operator may implement the network configuration change on the main network.

Abstract: A computer system obtains a data model that encodes a data source as a tree of logical tables. Each logical table includes respective data fields of the data source. For each data field in the logical tables, the system automatically assigns a semantic role to the data field based on a concept obtained from a concept graph, a data type of the data field, and data values of the data field. The system determines hierarchies between the data field and other data fields in the data source based on their respective semantic roles. The system validates the data field based on the assigned semantic role and the determined hierarchies. The system displays transformations to clean the data field based on the assigned semantic role. The system transforms data values for the data field according to a user input and updates the logical tables according to the transforming.

Abstract: A computer device receives a user input to specify a natural language command. In response to receiving the user input, the computer device generates a semantic interpretation for the natural language command using a trained word similarity model, based on semantic annotations for a published data source. The computer device queries the published data source based on the semantic interpretation, thereby retrieving a dataset. The computer device generates and displays a data visualization based on the retrieved dataset.

Abstract: A computing device receives, from a user of a first user group, input specifying a set of metadata comprising synonyms for data fields and data values of a data source. The computing device determines, in association with a second user group using a natural language interface, permission to access the set of metadata specified by the user of the first user group. The computing device, after determining that the second user group is permitted to access the set of metadata, receives a natural language command directed to the data source. The computing device interprets one or more terms in the command based on the set of metadata, and executes queries to retrieve data from the data source. The computing device generates and displays a data visualization in accordance with the retrieved data.

Abstract: A computing device is provided, including a processor that receives a network graph. The processor further receives a specification of a network traffic control heuristic for a network traffic routing problem over the network graph. The processor further constructs a gap maximization problem that has, as a maximization target, a difference between an exact solution to the network traffic routing problem and a heuristic solution generated using the network traffic control heuristic. The processor further generates a Lagrange multiplier formulation of the gap maximization problem. At a convex solver, the processor further computes an estimated maximum gap as an estimated solution to the Lagrange multiplier formulation of the gap maximization problem. The processor further performs a network traffic control action based at least in part on the estimated maximum gap.

Abstract: A computing device receives, in a graphical user interface, a first natural language query. The computing device parses the first natural language query, thereby identifying one or more keywords in the query. The computing device identifies one or more data sources that are relevant to the query. The computing device also identifies one or more data fields and/or data values from the data sources in the query. The computing device compares the keywords to respective trigger text for each of a plurality of data analysis templates, thereby selecting a first data analysis template. The first data analysis template includes a plurality of predefined data visualizations. The computing device generates a dashboard that includes the data visualizations using the identified data fields and/or data values, and displays the dashboard in the graphical user interface.

Abstract: The present application relates to a system, apparatus, and method of detecting anomalies in configurations of computer systems. A computer may execute a configuration analyzer to infer a configuration template that is applicable to multiple configuration files. The configuration analyzer configuration uses unsupervised learning on the configuration template to score parameters within each configuration file. The configuration analyzer indicates an anomaly for a parameter of a configuration file exceeding a threshold score. Inferring a configuration template may include generating a lowest cost template that is applicable to two of the multiple configuration files based on a cost function; and combining the lowest cost template with a subsequent configuration file of the multiple configuration files to generate an updated lowest cost template until the updated lowest cost template is applicable to all of the multiple configuration files.

Abstract: A method of measuring temperature of a battery having an internally disposed thermal protection arrangement is disclosed which includes providing at least one sensor holder having an electrode side and a housing side disposed within a housing, with at least one cavity provided on the electrode side, providing at least one temperature sensor placed in the at least one cavity of the at least one sensor holder, the outer surface of the at least one temperature sensor being flush with the remaining surface of the at least one sensor holder, attaching the at least one sensor holder to one of a first electrode or a second electrode of the battery, coupling the at least one temperature sensor to a header, and measuring the temperature of the battery.

Abstract: A pedal emulator including a housing having a first housing portion that defines a first chamber and a second housing portion that defines a second chamber, the second housing portion moveable relative to the first housing portion. The pedal emulator also includes a first spring that is compressed while the second housing portion travels a first distance relative to the first housing portion, a second spring that is compressed in parallel with the first spring after the second housing travels the first distance and while the second housing portion travels a second distance relative to the first housing portion, and a third spring that is compressed in parallel with the first spring and the second spring after the second housing portion travels the second distance and while the second housing portion travels a third distance relative to the first housing portion.