Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Types Of Transformers01:16

Types Of Transformers

976
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...
976
Transformers with Off-Nominal Turns Ratios01:25

Transformers with Off-Nominal Turns Ratios

152
In scenarios involving parallel transformers with disparate ratings, developing per-unit models requires accommodating off-nominal turns ratios. This situation arises when the selected base voltages are not proportional to the transformer’s voltage ratings. Consider a transformer where the rated voltages are related by the term a. If the chosen voltage bases satisfy a relationship involving term b, term c is defined as the ratio of these bases. This ratio is then substituted into the...
152
Transformers01:26

Transformers

1.1K
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...
1.1K
The Ideal Transformer01:26

The Ideal Transformer

393
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...
393
Stereotype Content Model02:16

Stereotype Content Model

14.7K
The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
14.7K
Source Transformation01:15

Source Transformation

6.4K
Source transformation is a fundamental technique employed in circuit analysis, offering a valuable tool for simplifying complex electrical circuits. This technique involves the replacement of either a voltage source in series with a resistor by a current source in parallel with a resistor, or vice versa. The key concept here is that when the original sources are deactivated (turned off), the equivalent resistance at the circuit's end terminals remains the same.
It is essential to note that when...
6.4K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Triboelectrification-Induced Self-Assembly of Macro-Sized Polymer Beads on a Nanostructured Surface for Self-Powered Patterning.

ACS nano·2018
Same author

Accommodating informative dropout and death: a joint modelling approach for longitudinal and semi-competing risks data.

Journal of the Royal Statistical Society. Series C, Applied statistics·2017
Same author

Ultraviolet-Ray-Induced Sea Cucumber (Stichopus japonicus) Melting Is Mediated by the Caspase-Dependent Mitochondrial Apoptotic Pathway.

Journal of agricultural and food chemistry·2017
Same author

Hydrogen Treatment Protects Mice Against Chronic Pancreatitis by Restoring Regulatory T Cells Loss.

Cellular physiology and biochemistry : international journal of experimental cellular physiology, biochemistry, and pharmacology·2017
Same author

Optimized ROI size on ADC measurements of normal pancreas, pancreatic cancer and mass-forming chronic pancreatitis.

Oncotarget·2017
Same author

Economic Evaluation of Lupus Nephritis in the Systemic Lupus International Collaborating Clinics Inception Cohort Using a Multistate Model Approach.

Arthritis care & research·2017
Same journal

Benchmarking the Robustness of Autonomous Driving to Environmental Illusions: A Lane Perception Perspective.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Learning Topology-Aware Representations via Test-Time Adaptation for Anomaly Segmentation.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

TraGraph-GS: Trajectory Graph-based Gaussian Splatting for Arbitrary Large-Scale Scene Rendering.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

SWIFT: A Small-World Interaction Framework for Flow-Aware Trajectory Prediction in Autonomous Driving.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

HardFlow: Hard-Constrained Sampling for Flow-Matching Models Via Trajectory Optimization.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Industrial Brain: Self-Evolving Neuro-Symbolic Autonomy with Causal Resilience for Cyber-Physical Systems.

IEEE transactions on pattern analysis and machine intelligence·2026
查看所有相关文章

相关实验视频

Updated: Jul 3, 2025

RBDT: A Computerized Task System based in Transposition for the Continuous Analysis of Relational Behavior Dynamics in Humans
11:09

RBDT: A Computerized Task System based in Transposition for the Continuous Analysis of Relational Behavior Dynamics in Humans

Published on: July 17, 2021

3.0K

智能:语法校准的多方面关系转换器用于变更标题化.

Yunbin Tu, Liang Li, Li Su

    IEEE transactions on pattern analysis and machine intelligence
    |February 13, 2024
    PubMed
    概括
    此摘要是机器生成的。

    这项研究引入了一种用于更改标题的新型变压器模型,有效地处理像视角更改这样的分心因素. 该方法可以更好地生成图像之间的语义变化的准确描述.

    更多相关视频

    Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities
    07:13

    Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities

    Published on: October 27, 2023

    1.1K
    Eye Tracking During Visually Situated Language Comprehension: Flexibility and Limitations in Uncovering Visual Context Effects
    07:36

    Eye Tracking During Visually Situated Language Comprehension: Flexibility and Limitations in Uncovering Visual Context Effects

    Published on: November 30, 2018

    15.7K

    相关实验视频

    Last Updated: Jul 3, 2025

    RBDT: A Computerized Task System based in Transposition for the Continuous Analysis of Relational Behavior Dynamics in Humans
    11:09

    RBDT: A Computerized Task System based in Transposition for the Continuous Analysis of Relational Behavior Dynamics in Humans

    Published on: July 17, 2021

    3.0K
    Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities
    07:13

    Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities

    Published on: October 27, 2023

    1.1K
    Eye Tracking During Visually Situated Language Comprehension: Flexibility and Limitations in Uncovering Visual Context Effects
    07:36

    Eye Tracking During Visually Situated Language Comprehension: Flexibility and Limitations in Uncovering Visual Context Effects

    Published on: November 30, 2018

    15.7K

    科学领域:

    • 计算机视觉 计算机视觉
    • 自然语言处理自然语言处理.
    • 人工智能的人工智能

    背景情况:

    • 修改标题描述了类似图像之间的语义差异.
    • 视角的变化和微弱的视觉变化信号对准确的变化描述构成挑战.

    研究的目的:

    • 开发一种强大的变更标题的方法,克服干扰因素并改善跨模式对齐.
    • 提高语义上准确和语言上连贯的变化描述的生成.

    主要方法:

    • 提出了一个语法校准的多方面关系转换器来学习有效的变化特征.
    • 采用多方面关系网络来探索细粒度的变化,并创建视图不变的表示.
    • 集成的部分语音 (POS) 知识与基于POS的视觉开关来校准变压器解码器,以实现可靠的交叉模式对齐.

    主要成果:

    • 拟议的方法通过探索语义和位置关系并加强全球对比对齐,有效地学习变化特征.
    • 语法校准的解码器动态利用基于word POS的视觉信息,实现可靠的跨模式对齐.
    • 在三个公共数据集上实现了最先进的性能,用于更改标题.

    结论:

    • 语法校准的多方面关系转换器提供了一个强大的方法,用于准确和强大的更改标题.
    • 将语言语法 (POS) 与视觉信息相结合,可以显著增强生成高层次变化描述.
    • 该方法在应对分散注意力和弱视觉变化信号所带来的挑战方面表现出卓越的表现.