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Related Concept Videos

Time-Series Graph00:54

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A time-series graph is a line graph with repeated measurements taken at successive intervals of time. It is also called a time series chart. To construct a time-series graph, one must look at both pieces of a paired data set. The horizontal axis is used to plot the time increments, and the vertical axis is used to plot the values of the variable that one is measuring. By using the axes in this way, each point on the graph will correspond to time and a measured quantity. The points on the graph...
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An ideal Y-Y transformer, grounded through neutral impedances, displays per-unit sequence networks akin to those of a single-phase ideal transformer when subjected to balanced positive- or negative-sequence currents. These currents do not produce neutral currents, and their associated voltage drops.
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Related Experiment Video

Updated: Jan 9, 2026

Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps
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EventBox: A Novel Visual Encoding for Interactive Analysis of Temporal and Multivariate Attributes in Event

Luis Montana, Jessica Magallanes, Miguel Juarez

    IEEE Transactions on Visualization and Computer Graphics
    |December 2, 2025
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    Summary

    EventBox, a new visual analytics method, enhances the analysis of event sequences by effectively visualizing temporal and multivariate attributes. This approach aids decision-making by revealing patterns and anomalies in complex data.

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    Area of Science:

    • Visual Analytics
    • Data Science
    • Human-Computer Interaction

    Background:

    • Event sequence data is rapidly growing across various domains.
    • Effective analysis methods are crucial for decision-making.
    • Existing visual analytics tools often neglect the interplay between temporal and multivariate attributes.

    Purpose of the Study:

    • To introduce EventBox, a novel data representation and visual encoding for analyzing event groups and their multivariate attributes.
    • To integrate EventBox into Sequen-C, a visual analytics system for event sequence analysis.
    • To enhance analytical depth with user-driven transformations and automated statistical analyses.

    Main Methods:

    • Developed EventBox for novel data representation and visual encoding.
    • Integrated EventBox into the Sequen-C visual analytics system.
    • Implemented user-driven transformations (alignment, sorting, substitution, aggregation) and automated statistical analyses.
    • Evaluated the approach using the ICE-T framework with 21 participants and real-world healthcare data case studies.

    Main Results:

    • EventBox effectively visualizes groups of events and their multivariate attributes.
    • User-driven transformations in Sequen-C enable agile EventBox creation.
    • Automated statistical analyses provide insights into attribute interaction significance.
    • Case studies with healthcare data demonstrated the revelation of meaningful patterns and anomalies.

    Conclusions:

    • The EventBox approach advances visual analytics for event sequence data.
    • It provides a flexible solution for exploring temporal and multivariate attributes.
    • The integrated Sequen-C system aids in identifying patterns, anomalies, and insights in complex event sequences.