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相关概念视频

Reducing Line Loss01:18

Reducing Line Loss

524
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.
With a step-up transformer at the source, the voltage is increased, thereby reducing the current in the transmission lines since power loss...
524
Classification of Systems-II01:31

Classification of Systems-II

651
Continuous-time systems have continuous input and output signals, with time measured continuously. These systems are generally defined by differential or algebraic equations. For instance, in an RC circuit, the relationship between input and output voltage is expressed through a differential equation derived from Ohm's law and the capacitor relation,
651
Transformers in Distribution System01:27

Transformers in Distribution System

682
Transformers in distribution systems can be broadly categorized into distribution substation transformers and other distribution transformers. They are crucial for stepping down high transmission voltages to levels suitable for distribution and end-user applications.
Distribution substation transformers come in various ratings and typically use mineral oil for insulation and cooling. To prevent moisture and air from entering the oil, some transformers use an inert gas like nitrogen to fill the...
682
Fast Decoupled and DC Powerflow01:24

Fast Decoupled and DC Powerflow

961
The fast decoupled power flow method addresses contingencies in power system operations, such as generator outages or transmission line failures. This method provides quick power flow solutions, essential for real-time system adjustments. Fast decoupled power flow algorithms simplify the Jacobian matrix by neglecting certain elements, leading to two sets of decoupled equations:
961
Per-Unit Sequence Models01:26

Per-Unit Sequence Models

527
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.
Zero-sequence currents, which are identical in magnitude and phase, generate a neutral current, resulting in voltage drops across the neutral impedance and the low-voltage winding. If the...
527
Instrument Transformers01:23

Instrument Transformers

778
Instrument transformers, comprising voltage transformers (VTs) and current transformers (CTs), play crucial roles in power substations by providing isolated replicas of current or voltage for measurement and protection purposes. Voltage transformers reduce the primary voltage to levels suitable for relay operation and measurement, while current transformers scale down the primary current. The primary winding of a current transformer often consists of a single turn, achieved by threading the...
778

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相关实验视频

Updated: May 1, 2026

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有效的WSI分类与序列减少和变压器预训练在文本上.

Juan I Pisula1,2, Katarzyna Bozek3,4,5

  • 1Institute for Biomedical Informatics, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany. juan.pisula@uk-koeln.de.

Scientific reports
|February 15, 2025
PubMed
概括
此摘要是机器生成的。

语言模型 (LMs) 现在在数字病理学 (WSI分类) 中脱而出. SeqShort是一种新的层,可以使用变压器高效地处理大型整片图像 (WSI),从而在最小的微调下实现准确的分类.

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科学领域:

  • 计算病理学计算病理学
  • 数字病理学数字病理学
  • 机器学习 机器学习

背景情况:

  • 语言模型 (LMs) 在各种顺序数据任务中表现出强的表现.
  • 数字病理学中的全幻灯片图像 (WSI) 分析适用于变压器架构.
  • 大型WSIs对深度变压器模型构成计算挑战.

研究的目的:

  • 开发一种使用深度变压器模型来分类WSIs的方法.
  • 为了解决处理大型WSIs的计算负担.
  • 为病理学任务利用经过文字预训练的转换器的知识.

主要方法:

  • 介绍SeqShort,一个基于多头注意力的序列缩短层.
  • 通过删除冗余的视觉信息,将大型WSIs总结为固定大小的特征向量的序列.
  • 将SeqShort应用到文本预训练的变压器模型中,用于WSI分类.

主要成果:

  • SeqShort有效地降低了对大输入的自我注意的计算成本.
  • 该方法允许在无序的图像补丁中包含位置编码.
  • 在不同的数字病理学任务中实现了准确的WSI分类.
  • 最小的微调 (小于参数的0.1%) 证明了有效的知识传输.

结论:

  • SeqShort 方便使用深度变压器模型进行WSI分类.
  • 从自然语言处理到数字病理学的知识转移是非常有效的.
  • 这种方法为大规模WSI分析提供了有效的解决方案.