A method including receiving a spatial query on spatial data. The spatial query has a spatial query extent including a sub-portion of the spatial data. A projection type is selected for the spatial query. A framebuffer is created for the selected projection type. Vertex buffers are established to hold a geometry of the selected projection type. The vertex buffers are passed from a CPU to a GPU. A spatial geometry of the spatial query extent is rendered into the framebuffer by projecting feature vertex data for features that fall at least partly within the spatial query extent into the vertex buffers. Rendering generates rendered framebuffer pixel values. Pixel values of the rendered framebuffer are retrieved as bytes on the CPU. A spatial query result is processed that includes or uses the pixel values.

The present invention provides a data processing method and an electronic terminal. The electronic terminal obtains target data that includes at least one data item, converts the target data into a data image by using a data visualization technology, and then sets the data image as wallpaper, where the data image includes at least one graphic element, and the graphic element is in a one-to-one correspondence with the data item. The target data is user data, and may include operation event information of operating the electronic terminal by a user, or information that is associated with a user account and that is based on at least one network platform, so as to automatically generate the wallpaper, show the user data to the user by using the wallpaper, and improve user experience.

A social media platform provides a map-based graphical user interface (GUI) with multiple geographically anchored icons that are selectable to trigger playback of respective galleries of ephemeral messages. Each of the plurality of location-based ephemeral galleries comprises media content contributed by multiple different users. The ephemeral galleries are compiled based on geotag data associated with respective ephemeral messages submitted by multiple users to be publicly viewable via the map-based GUI. Two or more different types of galleries are represented in the map-based GUI by different, visually distinct types of gallery icon.

A visualization device includes a processor for carrying out a first displaying process of displaying, on a display device, a first screen indicating power consumption of a whole of an equipment group in each of periods included in a period group, a second displaying process of displaying, on the display device, a second screen indicating a cycle time of each of pieces of equipment included in the equipment group in a particular period, and a third displaying process of displaying, on the display device, a third screen indicating a cycle time of each of processes carried out with use of a particular piece of equipment in the particular period.

An image processing device includes a hardware processor. The hardware processor designates, from one frame image of a dynamic image acquired by dynamic imaging of a movement of a locomotorium, a plurality of regions or points on a structure included in the locomotorium, sets an alignment reference based on the designated regions or points, tracks the designated regions or points in a plurality of frame images of the dynamic image, aligns a line segment connecting the regions or the points to each other in the plurality of frame images based on the alignment reference, and causes a display to display the line segment so as to be superimposed on a representative frame image of the dynamic image.

A system and method for detecting anomalies in very large datasets is disclosed. The method includes calculating statistics for data elements in a data set over a range of time periods. These statistics are arranged into a 2D array and analyzed using a machine learning algorithm to detect anomalous regions. The method also includes steps of analyzing time series of the data based on detected anomalous regions, correcting any errors in the datasets, and storing the corrected values in a separate database to maintain data integrity.

A system and method for detecting anomalies in very large datasets is disclosed. The method includes calculating statistics for data elements in a data set over a range of time periods. These statistics are arranged into a 2D array and analyzed using a machine learning algorithm to detect anomalous regions. The method also includes steps of analyzing time series of the data based on detected anomalous regions, correcting any errors in the datasets, and storing the corrected values in a separate database to maintain data integrity.

Methods and systems for presenting time series for analysis. A method may receive a first input defining a metric that indicates a relationship between a first and a second time series that are each associated with at least a first data object of a plurality of data objects, generate a first plot depicting the metric as determined from the first and the second time series, receive, via the user interface, a second input of a selection of a second data object of the plurality of data objects, determine, via an ontology, a relationship of the second data object with a third and a fourth time series that, respectively, are associated with series types that match series types associated with the first and the second time series, and generate and display, in the user interface, a second plot depicting the metric as determined from the third and the fourth time series.

Methods and systems for presenting time series for analysis. A method includes presenting a first visualization of summary information for an initial data set of a plurality of batches, presenting a filtered data set of the initial data set having a first batch identifier associated with a first batch and the second batch identifier associated with a second batch, executing a time series connector including transmitting a request to a time series application, the request comprising the first batch identifier, the second batch identifier, and the time series configuration data. The method further includes causing presentation of a user interface comprising a chart including a first plot for first time series data for the first batch identifier and a second plot for second time series data for the second batch identifier, the chart configured to the time series configuration data, and the first plot is aligned to the second plot.

A device includes a touch-sensitive display, one or more processors, and memory storing one or more programs including instructions for receiving data from an external device representing user input received over a duration of time at the external device. The programs may include instructions for determining whether the electronic device is actively executing an application for playback. The programs may further include instructions for in accordance with a determination that the electronic device is not actively executing an application for playback: displaying an indication of the receiving of the data; and displaying an affordance, wherein the affordance when selected launches the application for playback and causes the electronic device to playback the received data according to the duration of time of the user input.