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Related Concept Videos

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
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
Energy Losses in Transformers01:21

Energy Losses in Transformers

937
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...
937
Transformers in Distribution System01:27

Transformers in Distribution System

142
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...
142
Equivalent Circuits for Practical Transformers01:28

Equivalent Circuits for Practical Transformers

539
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...
539
Transformers with Off-Nominal Turns Ratios01:25

Transformers with Off-Nominal Turns Ratios

193
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...
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Reading comprehension based question answering system in Bangla language with transformer-based learning.

Tanjim Taharat Aurpa1,2, Richita Khandakar Rifat2, Md Shoaib Ahmed3

  • 1Department of Computer Science and Engineering, International University of Business Agriculture and Technology, Bangladesh.

Heliyon
|October 18, 2022
PubMed
Summary

This study introduces the first Bangla reading comprehension dataset and a question-answering system. Transformer models like BERT and ELECTRA show strong performance, achieving high accuracy for Bangla NLP tasks.

Keywords:
Bangla languageBangla question answeringBangla reading comprehensionReading comprehensionTransformer-based learning

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Area of Science:

  • Natural Language Processing (NLP)
  • Machine Learning
  • Artificial Intelligence

Background:

  • Question Answering (QA) systems are crucial for information retrieval.
  • Reading Comprehension (RC) is a popular NLP task, primarily developed in English.
  • No prior RC datasets or QA systems existed for the Bangla language.

Purpose of the Study:

  • To develop the first Bangla reading comprehension dataset.
  • To create a QA system for the Bangla language using RC.
  • To evaluate various deep learning models for Bangla QA.

Main Methods:

  • Constructed a new dataset with 3636 Bangla reading comprehension passages, questions, and answers.
  • Applied transformer-based deep neural network models, including LSTM, Bi-LSTM, RNN, ELECTRA, and BERT.
  • Trained and evaluated models on the constructed Bangla RC dataset.

Main Results:

  • Transformer architectures, specifically BERT and ELECTRA, outperformed other models.
  • The trained BERT model achieved 87.78% testing accuracy and 99% training accuracy.
  • The ELECTRA model achieved 82.5% training accuracy and 93% testing accuracy.

Conclusions:

  • The developed Bangla RC dataset and QA system are significant contributions to Bangla NLP.
  • BERT and ELECTRA demonstrate high efficacy for reading comprehension tasks in Bangla.
  • This work paves the way for advanced NLP research and applications in the Bangla language.