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相关概念视频

Types Of Transformers01:16

Types Of Transformers

1.1K
Transformers can provide desired voltages to a circuit by modifying the number of turns in the secondary windings.
If the ratio of the number of turns in the secondary winding to that of the primary winding is greater than one, then the transformer is said to be a step-up transformer. In a step-up transformer, the voltage at the secondary winding is greater than the voltage applied at the primary winding.
However, if this ratio is less than one, the transformer is said to be a step-down...
1.1K
The Ideal Transformer01:26

The Ideal Transformer

913
In single-phase two-winding transformers, two windings are coiled around a magnetic core characterized by cross-sectional area A and magnetic permeability μ. A phasor current i1 enters the left winding while i2 exits the right winding, establishing the fundamental working of the transformer through electromagnetic principles.
Ampere's Law forms the basis of understanding the magnetic field within the transformer. It states that the integral of the magnetic field intensity's...
913
Transformers in Distribution System01:27

Transformers in Distribution System

165
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...
165
Transformers01:26

Transformers

1.2K
A device that transforms voltages from one value to another using induction is called a transformer. A transformer consists of two separate coils, or windings, wrapped around the same soft iron core. However, they are electrically insulated from each other.
The iron core has a substantial relative permeability. Therefore, the magnetic field lines generated due to the current in one winding are almost entirely confined within the core, such that the same magnetic flux permeates each turn of both...
1.2K
Three-Winding Transformers01:19

Three-Winding Transformers

315
Three identical single-phase transformers can be configured to form a three-phase transformer connection, which involves high-voltage and low-voltage windings. The high-voltage windings are denoted by capital letters A-B-C, while the low-voltage windings are labeled with lowercase letters a-b-c, representing their respective phases. This notation helps distinguish between the high and low voltage sides of the transformer.
In the per-unit equivalent circuit of a grounded Y-Y three-phase...
315
Energy Losses in Transformers01:21

Energy Losses in Transformers

982
In an ideal transformer, it is assumed that there are no energy losses, and, hence, all the power at the primary winding is transferred to the secondary winding. However, in reality,  the transformers always have some energy losses, and, hence, the output power obtained at the secondary winding is less than the input power at the primary winding due to energy losses.
There are four main reasons for energy losses in transformers.
The first cause can be  the high resistance of the...
982

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Updated: Sep 17, 2025

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
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基于变压器网络的SEEG情感识别,具有通道选择和可解释性.

Zhuobin Yang, Xiaopeng Si, Weipeng Jin

    IEEE journal of biomedical and health informatics
    |July 3, 2025
    PubMed
    概括
    此摘要是机器生成的。

    一个基于空间变压器的新型混合网络 (STHN) 使用立体电脑图 (SEEG) 数据有效地识别情绪. 这种脑计算机接口 (BCI) 技术在治疗情绪障碍方面表现有前途.

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    相关实验视频

    Last Updated: Sep 17, 2025

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    Exploring the Use of Isolated Expressions and Film Clips to Evaluate Emotion Recognition by People with Traumatic Brain Injury
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    科学领域:

    • 神经科学是一个神经科学.
    • 生物医学工程 生物医学工程
    • 人工智能的人工智能

    背景情况:

    • 脑电脑接口 (BCI) 技术对于治疗耐火情绪障碍至关重要.
    • 立体电脑摄影 (SEEG) 从深层大脑结构和皮质提供精确的神经活动记录.
    • 对于开发情绪识别BCI,SEEG具有显著的潜力.

    研究的目的:

    • 使用SEEG数据开发和评估一种用于情绪识别的新算法.
    • 从九个受试者的SEEG记录中构建一个情绪数据集.
    • 根据现有方法评估拟议的基于空间变压器的混合网络 (STHN) 的性能.

    主要方法:

    • 收集了9名受试者的SEEG数据,以创建一个情绪数据集.
    • 开发了一个基于空间变压器的混合网络 (STHN) 用于SEEG情感识别.
    • 与基线方法 (如EEGNet,TSception和深卷积神经网络) 相比,评估了STHN的性能.

    主要成果:

    • STHN实现了83.56%的三重分类准确度,超过了基线方法.
    • STHN展示了道权重和选择能力,识别了用于情感识别的关键大脑区域.
    • 高重量通道主要位于与情绪相关的区域,如额叶,叶和海马,表明模型可解释性.

    结论:

    • 使用STHN开发的SEEG情绪识别算法是有效的,并提供一定程度的可解释性.
    • 这种新的方法在监测和治疗耐火情绪障碍患者方面具有重大潜力.
    • 这项研究代表了基于SEEG的情绪识别算法的首次开发.