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Related Concept Videos

Types Of Transformers01:16

Types Of Transformers

1.0K
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...
1.0K
The Ideal Transformer01:26

The Ideal Transformer

871
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...
871
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
Transformers in Distribution System01:27

Transformers in Distribution System

147
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...
147
Energy Losses in Transformers01:21

Energy Losses in Transformers

953
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...
953
Equivalent Circuits for Practical Transformers01:28

Equivalent Circuits for Practical Transformers

783
The practical equivalent circuits of single-phase two-winding transformers exhibit significant deviations from their idealized versions due to the inherent properties of winding resistance and finite core permeability. These properties result in real and reactive power losses, affecting the transformer's performance. Understanding these deviations is crucial for designing more efficient transformers.
In a practical transformer, each winding exhibits resistance and leakage reactance. The...
783

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News headline generation based on improved decoder from transformer.

Zhengpeng Li1, Jiansheng Wu2, Jiawei Miao1

  • 1University of Science and Technology Liaoning, Anshan, China.

Scientific Reports
|July 8, 2022
PubMed
Summary
This summary is machine-generated.

The proposed TD-NHG model enhances news headline generation by improving Transformer decoders, addressing issues like repetition and inaccurate summaries to create more accurate and diverse headlines.

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Area of Science:

  • Natural Language Processing
  • Artificial Intelligence

Background:

  • Traditional sequence-to-sequence and recurrent network models for news headline generation suffer from limited parallel processing and word repetition.
  • These limitations hinder the accurate summarization of news content, leading to ineffective headlines.

Purpose of the Study:

  • To introduce the TD-NHG model, an improved Transformer-based approach for news headline generation.
  • To enhance the accuracy and diversity of generated news headlines by overcoming existing model shortcomings.

Main Methods:

  • The TD-NHG model utilizes masked multi-head self-attention to capture features across news text representation subspaces.
  • Employing decoding strategies including top-k, top-p, and repetition-penalty mechanisms to refine headline generation.

Main Results:

  • Comparative experiments were conducted on the LCSTS and CSTS datasets.
  • The TD-NHG model achieved improved Rouge-1, Rouge-2, and Rouge-L scores compared to baseline methods.

Conclusions:

  • The TD-NHG model effectively improves the accuracy of news headline generation.
  • The proposed method demonstrates enhanced diversity in generated headlines, providing better news summarization.