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

Per-Unit Sequence Models01:26

Per-Unit Sequence Models

138
An ideal Y-Y transformer, grounded through neutral impedances, displays per-unit sequence networks akin to those of a single-phase ideal transformer when subjected to balanced positive- or negative-sequence currents. These currents do not produce neutral currents, and their associated voltage drops.
Zero-sequence currents, which are identical in magnitude and phase, generate a neutral current, resulting in voltage drops across the neutral impedance and the low-voltage winding. If the...
138
Associative Learning01:27

Associative Learning

640
Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
Classical conditioning, also known...
640
Observational Learning01:12

Observational Learning

360
Albert Bandura's observational learning, also known as imitation or modeling, occurs when a person observes and imitates another's behavior. It is a quicker process than operant conditioning. A well-known example is the Bobo doll study, where children who saw an adult acting aggressively towards the doll were more likely to act aggressively when left alone, compared to those who observed a nonaggressive adult. Many psychologists view observational learning as a form of latent learning...
360
Introduction to Learning01:18

Introduction to Learning

591
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...
591
Maxam-Gilbert Sequencing01:05

Maxam-Gilbert Sequencing

11.6K
In the same year as the discovery of the Sanger sequencing method, another group of scientists, Allan Maxam and Walter Gilbert, demonstrated their chemical-cleavage method for DNA sequencing. The Maxam-Gilbert method relies on using different chemicals that can cleave the DNA sequence at specific sites, the separation of resulting DNA fragments of variable size using electrophoresis, and deciphering the DNA sequence from the resulting gel bands.
Challenges of the Maxam-Gilbert Method
The...
11.6K
Sequence Networks of Rotating Machines01:24

Sequence Networks of Rotating Machines

165
A Y-connected synchronous generator, grounded through a neutral impedance, is designed to produce balanced internal phase voltages with only positive-sequence components. The generator's sequence networks include a source voltage that is exclusively in the positive-sequence network. The sequence components of line-to-ground voltages at the generator terminals illustrate this configuration.
Zero-sequence current induces a voltage drop across the generator's neutral impedance and other...
165

You might also read

Related Articles

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

Sort by
Same author

Molecular Simulation Study of the Adsorption Mechanism and Mechanical Properties at the Interface between Epoxy Resin and Phosphogypsum.

ACS omega·2025
See all related articles

Related Experiment Video

Updated: Oct 5, 2025

The "Motor" in Implicit Motor Sequence Learning: A Foot-stepping Serial Reaction Time Task
10:39

The "Motor" in Implicit Motor Sequence Learning: A Foot-stepping Serial Reaction Time Task

Published on: May 3, 2018

8.6K

Learning Damage Representations with Sequence-to-Sequence Models.

Qun Yang1, Dejian Shen2

  • 1Department of Civil and Environmental Engineering, The University of Auckland, Auckland 1023, New Zealand.

Sensors (Basel, Switzerland)
|January 22, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces a novel sequence-to-sequence (Seq2Seq) model for quantifying structural damage probability. The model effectively distinguishes damage representations and highlights areas of interest, improving post-hazard assessments.

Keywords:
Seq2Seq modeldamage detectiondeep learningstructural health monitoring

More Related Videos

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques
08:05

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques

Published on: June 30, 2020

7.7K
A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data
09:34

A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data

Published on: September 25, 2021

4.2K

Related Experiment Videos

Last Updated: Oct 5, 2025

The "Motor" in Implicit Motor Sequence Learning: A Foot-stepping Serial Reaction Time Task
10:39

The "Motor" in Implicit Motor Sequence Learning: A Foot-stepping Serial Reaction Time Task

Published on: May 3, 2018

8.6K
Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques
08:05

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques

Published on: June 30, 2020

7.7K
A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data
09:34

A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data

Published on: September 25, 2021

4.2K

Area of Science:

  • Structural Engineering
  • Artificial Intelligence
  • Civil Engineering

Background:

  • Natural hazards cause significant structural damage and economic losses globally.
  • Accurate and rapid post-hazard damage assessment is crucial for effective response.
  • Current data-driven damage detection models often classify damage states rather than quantifying them.

Purpose of the Study:

  • To develop a novel data-driven approach for quantifying structural damage probability.
  • To address the limitations of existing models that focus on damage classification.
  • To propose a sequence-to-sequence (Seq2Seq) model for damage quantification.

Main Methods:

  • A sequence-to-sequence (Seq2Seq) model was developed for damage quantification.
  • The model was trained using undamaged structural signals to learn normal behavior.
  • Damaged signals were fed into the trained model to quantify damage probability.

Main Results:

  • The proposed Seq2Seq model demonstrated a strong capability in distinguishing damage representations.
  • The model successfully quantified the probability of damage in structural signals.
  • The model effectively highlighted regions of interest within the structural signals, indicating damage.

Conclusions:

  • The developed Seq2Seq model offers a promising method for quantifying structural damage probability.
  • This approach enhances data-driven damage detection by moving beyond simple classification.
  • The model's ability to identify damage locations improves structural health monitoring and post-hazard analysis.