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

Multiple Comparison Tests01:13

Multiple Comparison Tests

Multiple comparison test, abbreviated as MCT, is a post hoc analysis generally performed after comparing multiple samples with one or more tests. An MCT will help identify a significantly different sample among multiple samples or a factor among multiple factors.
It would be easy to compare two samples using a significance alpha level of 0.05. In other words, there is only one sample pair to be compared. However, it would be difficult to identify a significantly different sample if the number...
Sign Test for Matched Pairs01:17

Sign Test for Matched Pairs

The sign test for matched pairs offers a robust method for comparing two paired samples, often for the effects of an intervention in one of them. This method is very useful in situations where the underlying distribution of the data is unknown. The test compares two related samples—often pre- and post-treatment measurements on the same subjects—to determine if there are significant differences in their median values.
To conduct the sign test, we first calculate the differences in value between...
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

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...
Wilcoxon Signed-Ranks Test for Matched Pairs01:09

Wilcoxon Signed-Ranks Test for Matched Pairs

The Wilcoxon signed-rank test for matched pairs evaluates the null hypothesis by combining the ranks of differences with their signs. It essentially tests whether the median of the differences in a population of matched pairs is zero. Since the test incorporates more information than the sign test, it generally yields more trustable conclusions. This test also does not require the data to follow a normal distribution, but two conditions must be met for it to be applicable: (1) the data must...
Trial and Error and Algorithm01:12

Trial and Error and Algorithm

A problem-solving strategy is a plan of action used to find a solution. Different strategies have distinct action plans. Trial and error involves trying different solutions until one works. For instance, to fix a broken printer, you might check ink levels, ensure the paper tray isn't jammed, and verify the printer's connection to your laptop. This method can be time-consuming but is commonly used. Thomas Edison, for example, used trial and error to find a suitable filament for the light bulb,...
Catalytically Perfect Enzymes01:07

Catalytically Perfect Enzymes

The theory of catalytically perfect enzymes was first proposed by W.J. Albery and J. R. Knowles in 1976. These enzymes catalyze biochemical reactions at high-speed. Their catalytic efficiency values range from 108-109 M-1s-1. These enzymes are also called 'diffusion-controlled' as the only rate-limiting step in the catalysis is that of the substrate diffusion into the active site. Examples include triose phosphate isomerase, fumarase, and superoxide dismutase.

You might also read

Related Articles

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

Sort by
Same author

Improving protein and protein interactions using pseudo-dimers derived from monomeric proteins.

Nature communications·2026
Same author

CRA5 a high-fidelity compressed reanalysis atmospheric dataset for weather and climate research.

Scientific data·2026
Same author

CrystalX: High-Accuracy Crystal Structure Analysis Using Deep Learning.

Journal of the American Chemical Society·2026
Same author

Evidential deep learning for interatomic potentials.

Nature communications·2025
Same author

Glasses-free 3D display with ultrawide viewing range using deep learning.

Nature·2025
Same author

TripoSG: High-Fidelity 3D Shape Synthesis Using Large-Scale Rectified Flow Models.

IEEE transactions on pattern analysis and machine intelligence·2025
Same journal

Relation DETR+: Exploring Explicit Position Relation Prior for Dense Prediction.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

RBF++: Quantifying and Optimizing Reasoning Boundaries across Measurable and Unmeasurable Capabilities for Chain-of-Thought Reasoning.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

CAFE: Cross-View Adaptive Fusion and Cluster Center Enhancement for Robust Multi-View Clustering.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

DIVER: Reinforced Diffusion Breaks Imitation Bottlenecks in End-to-End Autonomous Driving.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Ethics-Aware Safe Reinforcement Learning for Rare-Event Risk Control in Interactive Urban Driving.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Learning Shape Anchors for Holistic Indoor Scene Understanding.

IEEE transactions on pattern analysis and machine intelligence·2026
See all related articles

Related Experiment Videos

Performance Evaluation of Full Search Equivalent Pattern Matching Algorithms.

Wanli Ouyang, F Tombari, S Mattoccia

    IEEE Transactions on Pattern Analysis and Machine Intelligence
    |May 18, 2011
    PubMed
    Summary
    This summary is machine-generated.

    This study analyzes fast pattern matching algorithms that provide exact results. New algorithm extensions were developed, demonstrating superior performance in pattern matching tasks across various fields.

    Related Experiment Videos

    Area of Science:

    • Computer Science
    • Signal Processing
    • Image and Video Processing

    Background:

    • Pattern matching is a fundamental technique in signal processing, computer vision, and image/video processing.
    • Full search equivalent algorithms offer accelerated pattern matching while maintaining accuracy.

    Purpose of the Study:

    • To analyze and compare state-of-the-art algorithms for full search equivalent pattern matching.
    • To establish a benchmark dataset and testing methodology for future pattern matching algorithm evaluations.
    • To inspire the development of novel, high-speed pattern matching algorithms.

    Main Methods:

    • Evaluation and comparison of existing state-of-the-art full search equivalent pattern matching algorithms.
    • Development and testing of proposed extensions to these algorithms.
    • Utilizing comprehensive datasets and rigorous testing procedures.

    Main Results:

    • Identification of performance characteristics of current leading algorithms.
    • Demonstration that proposed algorithm extensions significantly outperform original formulations.
    • Establishment of a benchmark for future algorithm development and validation.

    Conclusions:

    • The proposed extensions offer enhanced performance for full search equivalent pattern matching.
    • The established benchmark will facilitate future research and development in the field.
    • This work provides a foundation for creating more efficient pattern matching solutions.