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

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

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

290
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...
290
Machines: Problem Solving II01:30

Machines: Problem Solving II

647
Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. Consider a lifting tong carrying a 100 kg load. It comprises movable sections DAF and CBG linked together with member AB.
647
Machines: Problem Solving I01:22

Machines: Problem Solving I

689
A toggle clamp is a mechanical device commonly used for holding and clamping objects in various applications, such as woodworking, metalworking, and assembly operations. Consider a toggle clamp subjected to a force of 200 N at the handle. The vertical clamping force can be calculated, provided the dimensions of the toggle clamp are known.
The toggle clamp system is a machine structure consisting of movable, pin-connected multi-force members that form a stabilized system to transmit forces. The...
689
Extraction: Partition and Distribution Coefficients01:14

Extraction: Partition and Distribution Coefficients

4.6K
The distribution law or Nernst's distribution law is the law that governs the distribution of a solute between two immiscible solvents. This law, also known as the partition law, states that if a solute is added to the mixture of two immiscible solvents at a constant temperature, the solute is distributed between the two solvents in such a way that the ratio of solute concentrations in the solvents remains constant at equilibrium.
For extracting a solute from an aqueous phase into an...
4.6K
Parallel Processing01:20

Parallel Processing

637
The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...
637
Cluster Sampling Method01:20

Cluster Sampling Method

14.0K
Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
14.0K

You might also read

Related Articles

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

Sort by
Same author

Phase-Locked Growth of Superconducting Ultrathin Monoclinic WS<sub>2</sub> Single Crystals via Chemical Vapor Deposition.

Advanced materials (Deerfield Beach, Fla.)·2026
Same author

Linear Peptidomimetics Containing Isoxazoline Scaffold: Design, Synthesis, Bioevaluation as Efficient Insecticidal Agents.

Journal of agricultural and food chemistry·2026
Same author

Fast Single-Nucleus Growth of Subcentimeter Monolayer MoS<sub>2</sub> Single Crystals via an All-in-One Precursor.

Journal of the American Chemical Society·2026
Same author

Effects of Different Tillage Measures on Soil Physical Properties, Organic Carbon Sequestration and Crop Production in Reclaimed Farmland Filled with Foreign Soil.

Plants (Basel, Switzerland)·2026
Same author

Thiol-disulfide exchange promotes Fe<sup>2+</sup>/Fe<sup>3+</sup> cycle to enhance peroxidase mimetic antibacterial activities of FeOCl.

Journal of colloid and interface science·2026
Same author

Direct growth of Co<sub>9</sub>S<sub>8</sub>@CoO<sub>x</sub> polyhedrons on highly oriented pyrolytic graphite as a cathode for water disinfection and pollutant degradation.

Journal of colloid and interface science·2026

Related Experiment Video

Updated: Jan 17, 2026

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

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

735

Multi-step partitioning combined with SOM neural network-based clustering technique effectively improves SAT solver

Siyu Yun1, Xinsheng Wang1

  • 1School of Information Science and Engineering, Harbin Institute of Technology at Weihai, Weihai, Shandong, China.

Peerj. Computer Science
|September 24, 2025
PubMed
Summary

This study introduces a novel strategy for Boolean Satisfiability Problem (SAT) solving by partitioning problems using structural information and a self-organizing map (SOM) neural network. This approach significantly accelerates SAT solver performance for electronic design automation (EDA).

Keywords:
ClusterDivideSATSOM neural networkStructural information

More Related Videos

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
12:27

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Published on: February 15, 2017

7.3K
Modeling the Functional Network for Spatial Navigation in the Human Brain
05:55

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

1.5K

Related Experiment Videos

Last Updated: Jan 17, 2026

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

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

735
Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
12:27

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Published on: February 15, 2017

7.3K
Modeling the Functional Network for Spatial Navigation in the Human Brain
05:55

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

1.5K

Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Electrical Engineering

Background:

  • The efficiency of Boolean Satisfiability Problem (SAT) solvers is critical for electronic design automation (EDA) tools.
  • Increasing integrated circuit scale makes SAT solvers a bottleneck in the circuit design cycle.
  • A gap exists between industrial SAT applications and pure research on solution algorithms.

Purpose of the Study:

  • To propose a new strategy for partitioning SAT problems based on structural information.
  • To enhance the speed and efficiency of SAT solvers in EDA.
  • To address the divergence between industrial SAT needs and research algorithms.

Main Methods:

  • Extracting structural information from SAT problems.
  • Employing a self-organizing map (SOM) neural network for problem partitioning.
  • Solving partitioned sub-problems with parallel solvers.

Main Results:

  • The proposed technique demonstrates stability and scalability.
  • The method significantly reduces the time required for solving industrial SAT benchmarks.
  • The SOM-based partitioning avoids complex parameter tuning.

Conclusions:

  • The structural partitioning strategy effectively accelerates SAT solver performance.
  • This approach offers a scalable solution for complex industrial circuit design challenges.
  • The technique bridges the gap between SAT research and industry application.