Jove
Visualize
Contact Us

Related Concept Videos

Improving Translational Accuracy02:07

Improving Translational Accuracy

11.7K
Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
11.7K
Long-term Potentiation01:35

Long-term Potentiation

55.5K
Long-term potentiation, or LTP, is one of the ways by which synaptic plasticity—changes in the strength of chemical synapses—can occur in the brain. LTP is the process of synaptic strengthening that occurs over time between pre- and postsynaptic neuronal connections. The synaptic strengthening of LTP works in opposition to the synaptic weakening of long-term depression (LTD) and together are the main mechanisms that underlie learning and memory.
55.5K
Longitudinal Research02:20

Longitudinal Research

12.0K
Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
12.0K
Classification of Signals01:30

Classification of Signals

622
In signal processing, signals are classified based on various characteristics: continuous-time versus discrete-time, periodic versus aperiodic, analog versus digital, and causal versus noncausal. Each category highlights distinct properties crucial for understanding and manipulating signals.
A continuous-time signal holds a value at every instant in time, representing information seamlessly. In contrast, a discrete-time signal holds values only at specific moments, often denoted as x(n), where...
622

You might also read

Related Articles

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

Sort by
Same author

The effect of remote ischemic preconditioning on postoperative gastrointestinal function recovery in patients undergoing gynecological laparoscopic surgery: a prospective randomized controlled trial.

BMC women's health·2026
Same author

Supramolecular Chloride Reservoirs Enable Homogeneous Halide Distribution and Near-Unity Blue Luminescence in Cs<sub>4</sub>PbBr<sub>6</sub>-CsPbBr<sub>3</sub> Heterostructured Perovskites.

Angewandte Chemie (International ed. in English)·2026
Same author

Constructing Fe<sub>3</sub>N/MnO heterojunction via heteroatom doping for degrading dye wastewater by heterogeneous electro-fenton system.

Journal of environmental sciences (China)·2026
Same author

Hydration and Microstructure Evolution of Acrylamide-Modified Tunnel Slag Mortar Under Various Curing Conditions.

Materials (Basel, Switzerland)·2026
Same author

NAMPT orchestrates fibroblast cuproptosis and immune crosstalk during IPF progression.

Frontiers in immunology·2026
Same author

Activation of peroxymonosulfate by distillers' grains biochar for the degradation of ciprofloxacin: critical roles of singlet oxygen and electron transfer.

RSC advances·2026
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 Experiment Video

Updated: Aug 11, 2025

Examining Online Syntactic Processing of Spoken Complex Sentences in Chinese Using Dual-Modal Interference Tasks
08:32

Examining Online Syntactic Processing of Spoken Complex Sentences in Chinese Using Dual-Modal Interference Tasks

Published on: September 5, 2019

5.7K

Feature-enhanced text-inception model for Chinese long text classification.

Guo Yang1, Yan Jiayu1, Xu Dongdong2

  • 1School of Electronic and Information Engineering, Nanjing University of Information Science and Technology, Nanjing, 210044, China.

Scientific Reports
|February 6, 2023
PubMed
Summary
This summary is machine-generated.

A new feature-enhanced text-inception model improves Chinese long text classification accuracy by addressing data imbalance. This deep learning approach achieves 93.97% accuracy, outperforming other models in recognizing text features.

More Related Videos

Interaction between Phonological and Semantic Processes in Visual Word Recognition using Electrophysiology
05:38

Interaction between Phonological and Semantic Processes in Visual Word Recognition using Electrophysiology

Published on: June 29, 2021

2.4K
Comparing the Frequency Effect Between the Lexical Decision and Naming Tasks in Chinese
08:08

Comparing the Frequency Effect Between the Lexical Decision and Naming Tasks in Chinese

Published on: April 1, 2016

9.4K

Related Experiment Videos

Last Updated: Aug 11, 2025

Examining Online Syntactic Processing of Spoken Complex Sentences in Chinese Using Dual-Modal Interference Tasks
08:32

Examining Online Syntactic Processing of Spoken Complex Sentences in Chinese Using Dual-Modal Interference Tasks

Published on: September 5, 2019

5.7K
Interaction between Phonological and Semantic Processes in Visual Word Recognition using Electrophysiology
05:38

Interaction between Phonological and Semantic Processes in Visual Word Recognition using Electrophysiology

Published on: June 29, 2021

2.4K
Comparing the Frequency Effect Between the Lexical Decision and Naming Tasks in Chinese
08:08

Comparing the Frequency Effect Between the Lexical Decision and Naming Tasks in Chinese

Published on: April 1, 2016

9.4K

Area of Science:

  • Natural Language Processing
  • Machine Learning
  • Deep Learning

Background:

  • Unbalanced distribution of multi-category Chinese long texts poses a challenge for accurate classification.
  • Existing models struggle to effectively capture both shallow and deep features in long Chinese texts.

Purpose of the Study:

  • To propose a novel data enhancement method and a feature-enhanced text-inception model for improved Chinese long text classification.
  • To enhance the accuracy and feature recognition capabilities for Chinese long text classification.

Main Methods:

  • A novel text-inception module was utilized for extracting shallow text features.
  • A deep feature extraction module combining bidirectional gated recurrent unit (Bi-GRU) and capsule neural network was employed for semantic understanding.
  • K-MaxPooling was applied for feature dimension reduction and enhancement.
  • Softmax function was used for final classification.

Main Results:

  • The proposed model significantly improves the accuracy of long Chinese text classification.
  • The model demonstrates a strong ability to recognize features within long Chinese texts.
  • Achieved an accuracy of 93.97% on an experimental dataset.

Conclusions:

  • The feature-enhanced text-inception model effectively addresses the challenge of unbalanced data distribution in Chinese long text classification.
  • The combination of shallow and deep feature extraction modules, along with K-MaxPooling, enhances classification performance.
  • The model offers a robust solution for accurate and reliable Chinese long text classification.