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

Transformers with Off-Nominal Turns Ratios01:25

Transformers with Off-Nominal Turns Ratios

147
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...
147
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

47
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
47
Woodward–Hoffmann Selection Rules and Microscopic Reversibility01:34

Woodward–Hoffmann Selection Rules and Microscopic Reversibility

3.0K
Electrocyclic reactions, cycloadditions, and sigmatropic rearrangements are concerted pericyclic reactions that proceed via a cyclic transition state. These reactions are stereospecific and regioselective. The stereochemistry of the products depends on the symmetry characteristics of the interacting orbitals and the reaction conditions. Accordingly, pericyclic reactions are classified as either symmetry-allowed or symmetry-forbidden. Woodward and Hoffmann presented the selection criteria for...
3.0K
PD Controller: Design01:26

PD Controller: Design

208
In automotive engineering, car suspension systems often employ Proportional Derivative (PD) controllers to enhance performance. PD controllers are utilized to adjust the damping force in response to road conditions. A controller, acting as an amplifier with a constant gain, demonstrates proportional control, with output directly mirroring input.
Designing a continuous-data controller requires selecting and linking components like adders and integrators, which are fundamental in Proportional,...
208
Per-Unit Sequence Models01:26

Per-Unit Sequence Models

73
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...
73
Transformers in Distribution System01:27

Transformers in Distribution System

99
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...
99

You might also read

Related Articles

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

Sort by
Same author

<b>Bats of the Vietnamese Mekong Delta: A revised checklist with significant new records</b>.

Zootaxa·2026
Same author

Effectiveness of silver diamine fluoride in managing hypersensitivity of molar-incisor hypomineralization affected molars: a scoping review.

Restorative dentistry & endodontics·2026
Same author

Lactucaindicas a-C: three newly identified compounds from <i>lactuca indica</i> L. that inhibit NO production.

Natural product research·2025
Same author

Three Previously Undescribed Compounds Isolated From the Leaves of Syzygium antisepticum With Their α-Glucosidase and Nitric Oxide Inhibitory Activity.

Chemistry & biodiversity·2025
Same author

Four New Compounds From Lactuca indica That Inhibit Nitric Oxide Production.

Chemistry & biodiversity·2025
Same author

Habitat prioritization for bat conservation: A case study in Vietnam.

PloS one·2025

Related Experiment Video

Updated: Jun 17, 2025

WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control
08:18

WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control

Published on: August 15, 2020

4.9K

A Hyper-Transformer model for Controllable Pareto Front Learning with Split Feasibility Constraints.

Tran Anh Tuan1, Nguyen Viet Dung1, Tran Ngoc Thang1

  • 1Faculty of Mathematics and Informatics, Hanoi University of Science and Technology; Center for Digital Technology and Economy (BK Fintech), Hanoi University of Science and Technology, Hanoi, Vietnam.

Neural Networks : the Official Journal of the International Neural Network Society
|August 9, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces a novel hyper-transformer model for Controllable Pareto Front Learning with Split Feasibility Constraints, improving accuracy in multi-objective optimization problems with constraints.

Keywords:
Controllable pareto front learningHypernetworkMulti-objective optimizationSplit feasibility problemTransformer

More Related Videos

A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions
07:34

A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions

Published on: March 25, 2014

9.9K
Using a Split-belt Treadmill to Evaluate Generalization of Human Locomotor Adaptation
08:04

Using a Split-belt Treadmill to Evaluate Generalization of Human Locomotor Adaptation

Published on: August 23, 2017

8.2K

Related Experiment Videos

Last Updated: Jun 17, 2025

WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control
08:18

WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control

Published on: August 15, 2020

4.9K
A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions
07:34

A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions

Published on: March 25, 2014

9.9K
Using a Split-belt Treadmill to Evaluate Generalization of Human Locomotor Adaptation
08:04

Using a Split-belt Treadmill to Evaluate Generalization of Human Locomotor Adaptation

Published on: August 23, 2017

8.2K

Area of Science:

  • Optimization
  • Machine Learning
  • Artificial Intelligence

Background:

  • Controllable Pareto Front Learning (CPFL) approximates Pareto optimal solutions.
  • Practical applications often involve decision-maker objectives within specific constraint regions.
  • Previous CPFL models utilized Hypernetwork-Multi-Layer Perceptron (Hyper-MLP) architectures.

Purpose of the Study:

  • To develop an advanced model for CPFL with Split Feasibility Constraints (SFC).
  • To leverage the advantages of Transformer architectures for improved performance in constrained multi-objective optimization.
  • To enhance the accuracy of approximating Pareto optimal solution sets under feasibility constraints.

Main Methods:

  • Development of a novel hyper-transformer (Hyper-Trans) model for CPFL with SFC.
  • Training the model specifically within the defined constraint region of the decision space.
  • Utilizing sequence-to-sequence universal approximation theory for model validation.

Main Results:

  • The proposed Hyper-Trans model demonstrated reduced Mean-Squared Error (MED) compared to the Hyper-MLP model.
  • The Hyper-Trans model effectively handles multi-objective optimization problems with split feasibility constraints.
  • Computational experiments confirmed the superior performance of the Hyper-Trans architecture.

Conclusions:

  • The hyper-transformer model offers a more accurate and effective approach for Controllable Pareto Front Learning with Split Feasibility Constraints.
  • This advancement enables better solutions for complex multi-objective optimization problems with practical constraints.
  • The findings suggest Transformers are a promising architecture for advanced optimization tasks.