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

Improving Translational Accuracy02:07

Improving Translational Accuracy

2.6K
2.6K
Leaky Scanning02:28

Leaky Scanning

5.1K
During most eukaryotic translation processes, the small 40S ribosome subunit scans an mRNA from its 5' end until it encounters the first start AUG codon. The large 60S ribosomal subunit then joins the smaller one to initiate protein synthesis. The location of the translation initiation is largely determined by the nucleotides near the start codon as there may be multiple translation initiation sites present on the mRNA.  Marilyn Kozak discovered that the sequence RCCAUGG (where R...
5.1K

You might also read

Related Articles

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

Sort by
Same author

Dual-Network Hydrogel for Atopic Dermatitis: Facile Construction from β-Lactoglobulin and Sustained Delivery of Dihydromyricetin.

Biomacromolecules·2026
Same author

Ergothioneine: An updated review on preparation strategies, biological activity and mechanisms, health and functional applications.

Food chemistry·2026
Same author

Hydration-mediated zwitterionic hydrogel electrolyte with hierarchical network for aqueous zinc ion batteries.

Journal of colloid and interface science·2026
Same author

[Corrigendum] ENO2 affects the EMT process of renal cell carcinoma and participates in the regulation of the immune micro-environment.

Oncology reports·2026
Same author

Cardiovascular outcome trials (CVOTs) in cardiorenal metabolic medicine: a decade of transformative progress (2016-2026).

Cardiovascular diabetology·2026
Same author

Risk factors and nomogram for cognitive impairment after stereotactic drainage of spontaneous intracerebral hemorrhage.

Frontiers in neurology·2026

Related Experiment Video

Updated: Jun 28, 2025

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

3.7K

The neural network algorithm-based quality assessment method for university English translation.

Min Gong1

  • 1School of Foreign Languages, Nanchang Institute of Technology, Nanchang, Jiangxi, China.

Network (Bristol, England)
|April 24, 2024
PubMed
Summary

Neural network algorithms offer consistent and transparent translation quality assessment in academia. This approach shows strong correlation with human evaluation, improving academic content accessibility and global discourse.

Keywords:
Translation quality assessmentaccuracyassessmentcommunicationknowledge exchangemachine learningneural networktranslation

More Related Videos

Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application
05:56

Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application

Published on: April 14, 2023

2.5K
Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

548

Related Experiment Videos

Last Updated: Jun 28, 2025

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

3.7K
Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application
05:56

Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application

Published on: April 14, 2023

2.5K
Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

548

Area of Science:

  • Computational Linguistics
  • Natural Language Processing
  • Artificial Intelligence in Education

Background:

  • Human evaluation of translation quality in academia is subjective and inconsistent.
  • Reliable translation quality assessment is vital for cross-cultural academic knowledge exchange.
  • Existing automated methods have limitations in capturing nuanced translation quality.

Purpose of the Study:

  • To introduce and evaluate a neural network-based model for assessing college-level English translation quality.
  • To compare the performance of the neural network model against human evaluators and traditional automated methods.
  • To explore the potential of artificial intelligence in enhancing the objectivity and efficiency of translation quality assessment.

Main Methods:

  • Development of a neural network model trained on college-level English translated academic papers.
  • Comparative analysis using human evaluators and a partial automated model as benchmarks.
  • Evaluation of the neural network model's performance using metrics such as accuracy, precision, F-measure, and recall.

Main Results:

  • A strong positive correlation (0.84) was found between the neural network model's assessments and human evaluations.
  • The Neural Network-Based Model outperformed Traditional Manual Evaluation and Partial Automated Model in key performance metrics.
  • The model demonstrated superior accuracy, precision, F-measure, and recall in translation quality evaluation.

Conclusions:

  • Neural network algorithms can provide a more consistent and transparent method for translation quality assessment in academia.
  • The developed model shows significant potential to revolutionize academic translation quality evaluation, enhancing content accessibility.
  • Further research is needed to address domain-specific adaptations and maximize the model's effectiveness for broader academic applications.