Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Relation between Mathematical Equations and Block Diagrams01:20

Relation between Mathematical Equations and Block Diagrams

3.2K
In a spring-mass-damper system, the second-order differential equation describes the dynamic behavior of the system. When transformed into the Laplace domain under zero initial conditions, this equation can be effectively analyzed and manipulated. The transformation into the Laplace domain converts differential equations into algebraic equations, simplifying the process of isolating the output.
3.2K
Block Diagram Reduction01:22

Block Diagram Reduction

727
The process of deriving the transfer function of a control system often involves reducing its block diagram to a single block. This simplification can be achieved through a series of strategic operations, including relocating branch points and comparators. These operations preserve the overall function of the system while allowing for easier manipulation and combination of blocks.
The first step in this process is the identification and relocation of a branch point. A branch point, where a...
727
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

544
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence of...
544
Introduction to Learning01:18

Introduction to Learning

1.6K
Learning is the process of acquiring knowledge or skills through practice or experience, leading to long-lasting behavioral changes. This acquisition occurs through interaction with the environment and requires practice or experience. For instance, mastering a skill such as surfing requires considerable practice and experience, highlighting the essential role of repeated interactions with the environment in learning.
In contrast to learned behaviors, unlearned behaviors such as crying, sexual...
1.6K
Cognitive Learning01:21

Cognitive Learning

1.6K
Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
Tolman introduced the idea that behavior is influenced by...
1.6K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Bangla-MedER: An annotated Bangla dataset for multi-type medical entity recognition from medical text.

Data in brief·2026
Same author

Transparent AI for mathematics: transformer-based large language models for mathematical entity relationship extraction with XAI.

Scientific reports·2026
Same author

Bangla MedER: Multi-BERT ensemble approach for the recognition of Bangla medical entity.

PloS one·2026
Same author

PROSHNO BINNASH: Contextual multi-label question answering dataset for low-resource NLP.

Data in brief·2025
Same author

Bangla-REX: A distinct dataset for Bangla relation extraction.

Data in brief·2025
Same author

NOIRBETTIK: A reading comprehension based multiple choice question answering dataset in Bangla language.

Data in brief·2025

Related Experiment Video

Updated: May 1, 2026

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
04:23

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images

Published on: April 21, 2023

1.8K

An ensemble novel architecture for Bangla Mathematical Entity Recognition (MER) using transformer based learning.

Tanjim Taharat Aurpa1, Md Shoaib Ahmed2,3

  • 1Department of Data Science, Bangabandhu Sheikh Mujibur Rahman Digital University, Bangladesh.

Heliyon
|February 15, 2024
PubMed
Summary

This study introduces Bangla Mathematical Entity Recognition (MER) using Bidirectional Encoder Representations from Transformers (BERT). The novel approach achieves high accuracy in identifying mathematical operators, operands, and terms in Bangla.

Keywords:
BERTBangla NLPBangla languageBangla mathematical entityEntity recognitionTransformer-based learning

More Related Videos

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

537
Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
04:48

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

401

Related Experiment Videos

Last Updated: May 1, 2026

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
04:23

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images

Published on: April 21, 2023

1.8K
Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

537
Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
04:48

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

401

Area of Science:

  • Natural Language Processing
  • Computational Linguistics
  • Artificial Intelligence

Background:

  • Mathematical entity recognition is crucial for machine understanding and processing of mathematical content.
  • Applications include automated theorem proving, knowledge retrieval, and educational platforms.
  • Mathematical entity recognition in the Bangla language is an unexplored area.

Purpose of the Study:

  • To develop and evaluate a system for Mathematical Entity Recognition (MER) in the Bangla language.
  • To identify mathematical operators, operands (numbers), and common mathematical terms.
  • To leverage deep learning, specifically Bidirectional Encoder Representations from Transformers (BERT), for this task.

Main Methods:

  • Utilized an ensemble architecture of deep neural networks based on BERT.
  • Created a novel dataset of 13,717 Bangla mathematical statements with annotated entities and types.
  • Employed accuracy, precision, recall, and F1-score as performance metrics.

Main Results:

  • Achieved a satisfactory accuracy of 97.98% using a single BERT model.
  • The ensemble BERT architecture demonstrated superior performance with an accuracy of 99.76%.
  • The system effectively recognized operators, operands, and mathematical terms.

Conclusions:

  • The proposed ensemble BERT model is highly effective for Bangla Mathematical Entity Recognition.
  • This work establishes a baseline for MER in the Bangla language.
  • The developed dataset and methodology can facilitate future research in multilingual mathematical NLP.