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Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
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In mechanical engineering, the stability of systems under various forces is critical for designing durable and efficient structures. One fundamental way to explore these concepts is by analyzing systems like two rods connected at a pivot point, O, with a torsional spring of spring constant k at the pivot point. This system is similar in appearance to a scissor jack used to change tires on a car. In this case, the arms of the linkage (equivalent to the rods in this system) are entirely vertical,...
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In the site survey of a four-sided traverse, internal angles are essential to ensure geometric accuracy. The survey revealed that the sum of the measured internal angles was 359 degrees and 48 minutes, which is 12 minutes less than the expected 360 degrees. This discrepancy signals an error likely arising from measurement inaccuracies during the fieldwork.To rectify this error, the adjustment process involved distributing the 12-minute shortfall equally across the four internal angles. By...
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Per-Unit Sequence Models01:26

Per-Unit Sequence Models

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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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SizePairs: Achieving Stable and Balanced Temporal Treemaps using Hierarchical Size-based Pairing.

Chang Han, Jaemin Jo, Anyi Li

    IEEE Transactions on Visualization and Computer Graphics
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    Summary

    SizePairs is a novel technique for creating stable and balanced treemaps that visualize hierarchical data over time. This method enhances visual quality and stability, outperforming existing methods in data visualization.

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    Area of Science:

    • Computer Science
    • Information Visualization
    • Data Analysis

    Background:

    • Treemaps are effective for visualizing hierarchical data, but maintaining stability and balance over time is challenging.
    • Existing techniques for time-dependent treemaps often struggle with visual quality and computational efficiency.

    Purpose of the Study:

    • To introduce SizePairs, a new algorithm for generating stable and balanced treemap layouts for time-varying hierarchical data.
    • To improve the visual quality and temporal stability of treemap visualizations.

    Main Methods:

    • SizePairs utilizes a hierarchical size-based pairing algorithm to recursively group nodes based on complementary size changes and similar sizes.
    • The algorithm optimizes splitting orientations and leaf node flipping to maximize visual quality and stability across time steps.

    Main Results:

    • SizePairs demonstrates superior performance in both visual quality and stability compared to state-of-the-art time-dependent treemap techniques.
    • The proposed method achieves high-quality layouts faster than the local moves technique.

    Conclusions:

    • SizePairs offers a significant advancement in visualizing dynamic hierarchical data with treemaps.
    • The technique provides a more stable, balanced, and visually appealing representation of temporal changes in hierarchical datasets.