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In a three-phase circuit, line loss is an indicator of energy dissipated as heat due to the resistance of transmission lines. To address this, incorporating transformers into the system—a step-up transformer at the source and a step-down transformer at the load—is a strategic solution. Two three-phase transformers are introduced to improve this.
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Vectors can be multiplied by scalars, added to other vectors, or subtracted from other vectors. The vector sum of two (or more) vectors is called the resultant vector or, for short, the resultant.
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The sign test for matched pairs offers a robust method for comparing two paired samples, often for the effects of an intervention in one of them. This method is very useful in situations where the underlying distribution of the data is unknown. The test compares two related samples—often pre- and post-treatment measurements on the same subjects—to determine if there are significant differences in their median values.
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A Y-connected synchronous generator, grounded through a neutral impedance, is designed to produce balanced internal phase voltages with only positive-sequence components. The generator's sequence networks include a source voltage that is exclusively in the positive-sequence network. The sequence components of line-to-ground voltages at the generator terminals illustrate this configuration.
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The process of deriving the transfer function of a control system often involves reducing its block diagram to a single block. This simplification can be achieved through a series of strategic operations, including relocating branch points and comparators. These operations preserve the overall function of the system while allowing for easier manipulation and combination of blocks.
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A Gran plot is used to predict the equivalence volume or endpoint of a potentiometric or acid-base titration without reaching the endpoint. Typically, titration data is collected as a function of the titrant's volume up to a point less than the equivalence volume and then transformed into a linear format. The straight line is extended to the x-axis, indicating the necessary titrant volume to achieve the equivalence point.
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通过线性优化进行链接符号预测的签名子图编码方法.

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    此摘要是机器生成的。

    我们引入了一种新的方法,通过线性优化 (SELO) 进行子图编码,用于在签名网络中预测链接符号. SELO的表现优于当前最先进的模型,在预测链接信号方面表现出卓越的表现.

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    科学领域:

    • 图形神经网络的神经网络
    • 网络科学 网络科学
    • 机器学习 机器学习

    背景情况:

    • 符号网络代表具有正或负符号的关系.
    • 链接标志预测对于理解网络结构至关重要.
    • 目前的方法,如签名定向图形神经网络 (SDGNNs),表现强.

    研究的目的:

    • 提出一个新的架构,用于链接标志预测在签名定向网络.
    • 通过线性优化 (SELO) 模型引入子图编码.
    • 用最先进的方法来评估SELO的表现.

    主要方法:

    • 开发了一个子图编码方法来学习边缘嵌入.
    • 利用线性优化 (LO) 方法将子图嵌入到概率矩阵中.
    • 在5个现实世界签名网络上进行了实验.

    主要成果:

    • 与SDGNN相比,SELO取得了领先的预测性能.
    • 该模型的性能优于现有的基于特征和基于嵌入的方法.
    • 在所有五个网络和四个评估指标 (AUC,F1,微F1,宏F1) 中都观察到持续的改善.

    结论:

    • 对于已签名的定向网络,SELO在链接标志预测方面取得了重大进展.
    • 通过线性优化方法进行子图编码对于学习边缘嵌入是有效的.
    • 拟议的模型在各种真实世界数据集中展示了强大而卓越的性能.