Jove
Visualize
Contact Us

Related Concept Videos

Synthesis and Decomposition Reactions02:17

Synthesis and Decomposition Reactions

38.2K
Synthesis and decomposition are two types of redox reactions. Synthesis means to make something, whereas decomposition means to break something. The reactions are accompanied by chemical and energy changes. 
38.2K
Real-World Application of Classical Conditioning01:15

Real-World Application of Classical Conditioning

1.3K
Classical conditioning not only includes the initial pairing of stimuli but also extends to more complex forms, such as higher-order conditioning. Higher-order conditioning involves creating associations beyond the primary conditioned stimulus, resulting in a chain of conditioned responses.
Higher-order, or second-order, conditioning occurs when a neutral stimulus becomes associated with an already established conditioned stimulus through repeated pairings. For instance, if a dog has been...
1.3K
Real Time RT-PCR02:57

Real Time RT-PCR

65.1K
Real-time reverse transcription-polymerase chain reaction, or Real-time RT-PCR, is an analytical tool used to determine the expression level of target genes. The method involves converting mRNA to complementary DNA with the help of an enzyme known as reverse transcriptase, followed by the PCR amplification of the cDNA. These two processes can be performed simultaneously in a single tube or separately as a two-step reaction.
The real-time quantification of the number of amplified products is...
65.1K
What is a Mode?01:07

What is a Mode?

26.0K
The mode is one of the commonly used measures of a central tendency. It is defined as the most frequent value in a data set.
There can be more than one mode in a data set if multiple values have the same highest frequency. For instance, suppose that the Statistics exam scores of 20 students are: 50; 53; 59; 59; 63; 63; 72; 72; 72; 72; 72; 76; 78; 81; 83; 84; 84; 84; 90; 93. Here, the mode is 72, as it occurs most frequently, five times.
A data set with two modes is called bimodal. For example,...
26.0K
Empirical Method to Interpret Standard Deviation01:09

Empirical Method to Interpret Standard Deviation

10.2K
The empirical rule, also known as the three-sigma rule, allows a statistician to interpret the standard deviation in a normally distributed dataset. The rule states that 68% of the data lies within one standard deviation from the mean, 95% lies within two standard deviations from the mean, and 99.7% lies within three standard deviations from the mean. Additionally, this rule is also called the 68-95-99.7 rule.
This rule is used widely in statistics to calculate the proportion of data values...
10.2K
Nursing Implementation01:15

Nursing Implementation

6.2K
Implementation is the execution of the nursing care plan developed during the planning phase.
The five steps to implementing effective nursing care include reassessing the patient, reviewing and revising the existing nursing care plan, organizing the resources and care delivery, anticipating and preventing complications, and implementing nursing interventions.
6.2K

You might also read

Related Articles

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

Sort by
Same author

Design and development of ultrasonic bipolar square-wave pulser for non-destructive testing of concrete structures.

The Review of scientific instruments·2020
Same author

Real-time imaging of immersed fuel-sub assemblies using multi-channel ultrasonic camera.

The Review of scientific instruments·2020
See all related articles
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: Jan 31, 2026

Ultrasonic Fatigue Testing in the Tension-Compression Mode
06:54

Ultrasonic Fatigue Testing in the Tension-Compression Mode

Published on: March 7, 2018

11.2K

Real time implementation of empirical mode decomposition algorithm for ultrasonic nondestructive testing

Eaglekumar G Tarpara1, V H Patankar1

  • 1Homi Bhabha National Institute (HBNI), Mumbai 400094, India.

The Review of Scientific Instruments
|January 3, 2019
PubMed
Summary

A new real-time empirical mode decomposition (EMD) algorithm enhances ultrasonic non-destructive testing (NDT). This visual software implementation improves signal-to-noise ratio in noisy environments for better pulse-echo signal identification.

More Related Videos

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

8.1K
The Participant-Reported Implementation Update and Score PRIUS: A Novel Method for Capturing Implementation-Related Data Over Time
06:05

The Participant-Reported Implementation Update and Score PRIUS: A Novel Method for Capturing Implementation-Related Data Over Time

Published on: February 19, 2021

1.8K

Related Experiment Videos

Last Updated: Jan 31, 2026

Ultrasonic Fatigue Testing in the Tension-Compression Mode
06:54

Ultrasonic Fatigue Testing in the Tension-Compression Mode

Published on: March 7, 2018

11.2K
Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

8.1K
The Participant-Reported Implementation Update and Score PRIUS: A Novel Method for Capturing Implementation-Related Data Over Time
06:05

The Participant-Reported Implementation Update and Score PRIUS: A Novel Method for Capturing Implementation-Related Data Over Time

Published on: February 19, 2021

1.8K

Area of Science:

  • Engineering
  • Signal Processing
  • Materials Science

Background:

  • Empirical Mode Decomposition (EMD) is challenging for real-time applications due to its data-driven nature and extensive computations.
  • Non-destructive testing (NDT) using ultrasonic imaging requires efficient signal processing for accurate defect detection.
  • Real-time signal analysis is crucial for improving the efficiency and reliability of NDT systems.

Purpose of the Study:

  • To develop and implement a real-time Empirical Mode Decomposition (EMD) algorithm for ultrasonic non-destructive testing (NDT).
  • To evaluate the performance of EMD with different interpolation methods (piecewise linear and cubic spline) for real-time processing.
  • To demonstrate the effectiveness of the developed system in enhancing ultrasonic A-scan data resolution and signal-to-noise ratio.

Main Methods:

  • Implementation of the EMD algorithm in a visual software environment.
  • Comparison of piecewise linear interpolation (PLI) and cubic spline interpolation (CSI) methods for EMD.
  • Utilizing the Thomas algorithm to solve the cubic spline tridiagonal matrix for real-time processing.
  • Adoption of a partial reconstruction algorithm for signal filtering, including baseline correction and noise reduction.

Main Results:

  • The time complexity for both PLI and CSI based EMD methods was computed, enabling real-time processing.
  • The developed EMD-based visual software successfully performed baseline correction and noise filtering.
  • Ultrasonic NDT experimentation validated the real-time practicability and efficiency of the method.
  • Significant improvement in the time-domain resolution of ultrasonic A-scan raw data was achieved.

Conclusions:

  • The real-time EMD algorithm provides an efficient solution for signal processing in ultrasonic NDT.
  • The system effectively enhances the signal-to-noise ratio in noisy environments, improving visualization and identification of ultrasonic pulse-echo signals.
  • This approach offers a practical and efficient method for real-time ultrasonic imaging and analysis in NDT applications.