Abstract: A device and a method for continuous desulphurisation of liquid iron provided by a blast furnace process or a direct reduction process.

Abstract: A method includes the following steps. A video sequence including detection results from one or more detectors is received, the detection results identifying one or more objects. A clustering framework is applied to the detection results to identify one or more clusters associated with the one or more objects. The clustering framework is applied to the video sequence on a frame-by-frame basis. Spatial and temporal information for each of the one or more clusters are determined. The one or more clusters are associated to the detection results based on the spatial and temporal information in consecutive frames of the video sequence to generate tracking information. One or more target tracks are generated based on the tracking information for the one or more clusters. The one or more target tracks are consolidated to generate refined tracks for the one or more objects.

Abstract: Techniques are described for headlessly completing a task of an application in the background of a digital personal assistant. For example, a method can include receiving a voice input via a microphone. Natural language processing can be performed using the voice input to determine a user voice command. The user voice command can include a request to perform a task of the application. The application can be caused to execute the task as a background process without a user interface of the application appearing. A user interface of the digital personal assistant can provide a response to the user, based on a received state associated with the task, so that the response comes from within a context of the user interface of the digital personal assistant without surfacing the user interface of the application.

Abstract: A method includes the following steps. A video sequence including detection results from one or more detectors is received, the detection results identifying one or more objects. A clustering framework is applied to the detection results to identify one or more clusters associated with the one or more objects. The clustering framework is applied to the video sequence on a frame-by-frame basis. Spatial and temporal information for each of the one or more clusters are determined. The one or more clusters are associated to the detection results based on the spatial and temporal information in consecutive frames of the video sequence to generate tracking information. One or more target tracks are generated based on the tracking information for the one or more clusters. The one or more target tracks are consolidated to generate refined tracks for the one or more objects.

Abstract: A method includes the following steps. A video sequence including detection results from one or more detectors is received, the detection results identifying one or more objects. A clustering framework is applied to the detection results to identify one or more clusters associated with the one or more objects. The clustering framework is applied to the video sequence on a frame-by-frame basis. Spatial and temporal information for each of the one or more clusters are determined. The one or more clusters are associated to the detection results based on the spatial and temporal information in consecutive frames of the video sequence to generate tracking information. One or more target tracks are generated based on the tracking information for the one or more clusters. The one or more target tracks are consolidated to generate refined tracks for the one or more objects.

Abstract: A method includes the following steps. A video sequence including detection results from one or more detectors is received, the detection results identifying one or more objects. A clustering framework is applied to the detection results to identify one or more clusters associated with the one or more objects. The clustering framework is applied to the video sequence on a frame-by-frame basis. Spatial and temporal information for each of the one or more clusters are determined. The one or more clusters are associated to the detection results based on the spatial and temporal information in consecutive frames of the video sequence to generate tracking information. One or more target tracks are generated based on the tracking information for the one or more clusters. The one or more target tracks are consolidated to generate refined tracks for the one or more objects.

Abstract: Techniques are described for headlessly completing a task of an application in the background of a digital personal assistant. For example, a method can include receiving a voice input via a microphone. Natural language processing can be performed using the voice input to determine a user voice command. The user voice command can include a request to perform a task of the application. The application can be caused to execute the task as a background process without a user interface of the application appearing. A user interface of the digital personal assistant can provide a response to the user, based on a received state associated with the task, so that the response comes from within a context of the user interface of the digital personal assistant without surfacing the user interface of the application.

Abstract: The described implementations relate to updating views in a database system. One implementation can identify an active view that retrieves records from a database and determine one or more physical tables in the database that are referenced by the active view. The implementation can track one or more columns in the physical tables that are used by the active view and identify a change to the physical tables in a transaction log of the database. If the change does not affect the one or more columns, the change can be treated as an ignorable change for the active view.

Abstract: The described implementations relate to updating views in a database system. One implementation can identify an active view that retrieves records from a database and determine one or more physical tables in the database that are referenced by the active view. The implementation can track one or more columns in the physical tables that are used by the active view and identify a change to the physical tables in a transaction log of the database. If the change does not affect the one or more columns, the change can be treated as an ignorable change for the active view.

Abstract: The described implementations relate to updating views in a database system. One implementation can identify an active view that retrieves records from a database and determine one or more physical tables in the database that are referenced by the active view. The implementation can track one or more columns in the physical tables that are used by the active view and identify a change to the physical tables in a transaction log of the database. If the change does not affect the one or more columns, the change can be treated as an ignorable change for the active view.

Abstract: The described implementations relate to updating views in a database system. One implementation can identify an active view that retrieves records from a database and determine one or more physical tables in the database that are referenced by the active view. The implementation can track one or more columns in the physical tables that are used by the active view and identify a change to the physical tables in a transaction log of the database. If the change does not affect the one or more columns, the change can be treated as an ignorable change for the active view.

Abstract: The described implementations relate to updating views in a database system. One implementation can identify an active view that retrieves records from a database and determine one or more physical tables in the database that are referenced by the active view. The implementation can track one or more columns in the physical tables that are used by the active view and identify a change to the physical tables in a transaction log of the database. If the change does not affect the one or more columns, the change can be treated as an ignorable change for the active view.

Abstract: The described implementations relate to secure and verifiable data handling. One implementation can receive a request to add information from a drop-off site to a user account. The request can include a location element and a security element. This implementation can also obtain encrypted units of the referenced data from the drop-off site based upon the location element. This implementation can associate the information with the user account and store the security element.

Abstract: The described implementations relate to secure and verifiable data handling. One implementation can receive a request to upload information, wherein the information includes a referencing element and at least one blob of referenced data. This implementation can also receive a chunk of an individual blob. The chunk can include multiple blocks. Individual blocks can be hashed. Upon receipt of an indication that all chunks have been uploaded, this implementation can create an overall hash of the information from the block hashes rather than from the information.

Abstract: A proximal humeral prosthesis includes a humeral head having a distal end and a proximal end adapted to be coupled to a glenoid cavity of a scapula; a humeral stem core having an outer surface, a distal end, and a proximal end adapted to be coupled to the distal end of the humeral head; a humeral stem graft having an inner surface adapted to be coupled to at least a portion of the outer surface of the humeral stem core, a distal end, a proximal end, and an outer surface including at least one tendon attachment site; and an intramedullary stem having a proximal end adapted to be coupled to the distal end of the humeral stem core and a distal end adapted to be coupled to at least one bone of a skeleton. The prosthesis can be rendered modular and can further include a spacer segment. Resorption of bone from the humeral stem graft can be inhibited by compression of the humeral stem graft.