Abstract: Automatic data modeling in a low-latency data access and analysis system includes identifying an analytical-object in response to first data expressing usage intent, generating an analytical model generation data-query for the analytical-object, obtaining a trained analytical model generated in accordance with the analytical model generation query and trained using results data obtained in accordance with the analytical-object, generating a resolved-request representing second data expressing usage intent and indicating a request for results data obtained using the trained analytical model, generating an analytical model results data-query for obtaining the results data in accordance with the trained analytical model and the analytical-object, and outputting data for presenting a visualization of the results data obtained by executing the analytical model results data-query, wherein a first portion of the results data corresponds with the analytical-object and a second portion of the results data corresponds

Abstract: Automatic data modeling in a low-latency data access and analysis system includes identifying an analytical-object in response to first data expressing usage intent, generating an analytical model generation data-query for the analytical-object, obtaining a trained analytical model generated in accordance with the analytical model generation query and trained using results data obtained in accordance with the analytical-object, generating a resolved-request representing second data expressing usage intent and indicating a request for results data obtained using the trained analytical model, generating an analytical model results data-query for obtaining the results data in accordance with the trained analytical model and the analytical-object, and outputting data for presenting a visualization of the results data obtained by executing the analytical model results data-query, wherein a first portion of the results data corresponds with the analytical-object and a second portion of the results data corresponds

Abstract: A charging system for an electric vehicle includes: a rechargeable energy storage device adapted to store electrical energy and to supply the stored electrical energy to at least one electric motor of the vehicle to propel the vehicle; a charger adapted to supply electrical energy to the energy storage device according to a selectable power rating of at least two power ratings to charge and/or recharge the energy storage device based on a selected one of power ratings; and a controller adapted to select one of the power ratings of the charger to set the charger to charge and/or recharge the energy storage device based on the selected one of the power ratings.

Abstract: Object scriptability includes receiving a high-level language script describing at least one data-analysis object, including a node representing the data-analysis object in a graph-based data structure including a plurality of nodes, where each node from the plurality of nodes represents a respective data-analysis object in a data analysis system, where each node from the plurality of nodes is connected to at least one other node from the plurality of nodes by an edge, and where the edge represents a relationship between the respective objects in the data analysis system.

Abstract: Object scriptability methods and system are described herein. The method includes generating a graph-based data structure including a plurality of nodes, where each node from the plurality of nodes represents a respective data-analysis object in a data analysis system, where each node from the plurality of nodes is connected to at least one other node from the plurality of nodes by an edge, where the edge represents a relationship between the respective objects in the data analysis system, and where generating the graph-based data structure includes receiving a high-level language script describing at least one data-analysis object, and generating at least one node from the plurality of nodes in accordance with the high-level language script.

Abstract: Object scriptability methods and system are described herein. The method includes generating a graph-based data structure including a plurality of nodes, where each node from the plurality of nodes represents a respective data-analysis object in a data analysis system, where each node from the plurality of nodes is connected to at least one other node from the plurality of nodes by an edge, where the edge represents a relationship between the respective objects in the data analysis system, and where generating the graph-based data structure includes receiving a high-level language script describing at least one data-analysis object, and generating at least one node from the plurality of nodes in accordance with the high-level language script.

Abstract: An improved optical method for determining metal or a metal compound thereof in a sample with organic impurities. The optical method comprises of solvating the metal in a liquid medium and then mixing this liquid medium with an optical indicator and then measuring the presence of the metal. The improvement lies in removing any organic impurities by the addition of an additive, where the said additive is removed before the optical indicator is added.

Abstract: An improved optical method for determining metal or a metal compound thereof in a sample with organic impurities. The optical method comprises of solvating the metal in a liquid medium and then mixing this liquid medium with an optical indicator and then measuring the presence of the metal. The improvement lies in removing any organic impurities by the addition of an additive, where the said additive is removed before the optical indicator is added.