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

Non-destructive Tests for Concrete Strength01:12

Non-destructive Tests for Concrete Strength

104
The rebound hammer test, also known as the Schmidt hammer test, is a non-destructive technique for evaluating the hardness of concrete and, indirectly, the strength of concrete. It operates on the principle that the rebound of a spring-driven mass from a concrete surface correlates to the surface's hardness. The device comprises a mass within a tubular housing, a spring mechanism, and a plunger that strikes the concrete. Upon release, the energy imparted to the mass by the spring causes it...
104
Prediction Intervals01:03

Prediction Intervals

2.2K
The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y. 
2.2K
Classification of Bones01:18

Classification of Bones

4.9K
The bones of the human skeletal system are of varied shapes, sizes, and functions. They can be classified based on their shape and function into four major classes: long bones, short bones, flat bones, and irregular bones. Some classifications include a fifth type, the sesamoid bones, as a separate class, whereas others categorize them under short bones.
Long and Short Bones
The appendicular skeleton, particularly the upper and lower limbs, is primarily made of long and short bones. The...
4.9K
Toughness and Hardness of Aggregate01:22

Toughness and Hardness of Aggregate

237
Toughness and hardness are critical properties of aggregate materials used in concrete, particularly on pavement surfaces and industrial flooring subjected to heavy loads. Toughness is defined as the aggregate's resistance to failure by impact and is measured by the aggregate impact value (AIV). For this, the aggregate impact value test is performed, wherein the impact is delivered by a standard hammer, which falls freely under its own weight onto the aggregates. The aggregates fragment in...
237
Dynamic Modulus of Elasticity of Concrete01:16

Dynamic Modulus of Elasticity of Concrete

250
The dynamic modulus of elasticity assesses how a concrete structure deforms under impact or dynamic loads. It is typically higher than the static modulus of elasticity, measured under slow, steady loading conditions.
The sonic test is a common method to determine the dynamic modulus. In this test, a concrete beam, sized either 6 x 6 x 30 inches or 4 x 4 x 20 inches, is clamped at its center. Vibrations are initiated at one end of the beam by an electromagnetic exciter unit powered by...
250
Elasticity in Concrete01:20

Elasticity in Concrete

80
Upon subjecting concrete to moderate or high uniaxial compressive or tensile stresses, the strain response is non-linear relative to the stress applied. As the stress is removed, the resulting stress-strain curve deviates from the original path traced during loading, creating a hysteresis loop, indicative of the concrete's non-linear and non-elastic properties. Typically, a material's modulus of elasticity, which is a measure of the material's stiffness, is inferred from the linear...
80

You might also read

Related Articles

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

Sort by
Same author

Directional Charge Transfer in V-P-Ni 1D Chain for CO<sub>2</sub> Photoreduction and Mustard-Gas Simulant Detoxification.

Inorganic chemistry·2026
Same author

Basal Medium Affects the Biological Characteristics and Immunomodulatory Functions of MSCs.

Applied biochemistry and biotechnology·2026
Same author

Effects of Internet-Based Lifestyle Interventions on Nonalcoholic Fatty Liver Disease: A Meta-Analysis of Randomized Controlled Trials.

Canadian journal of gastroenterology & hepatology·2026
Same author

Artificial human stem cell niche created in cartilage-inspired hydrogel for enhanced articular cartilage regeneration.

Biomaterials·2026
Same author

Insights into Nutrient Contents, Fermentation Profiles, Bacterial Communities and Co-Occurrence Network of Small-Bale Oat Silage Prepared with/Without <i>Lentilactobacillus buchneri</i> or <i>Lacticaseibacillus rhamnosus</i>.

Microorganisms·2026
Same author

Human Umbilical Cord Mesenchymal Stem Cells Ameliorate Cognitive Decline by Restoring Senescent Microglial Function via NF-κB-SREBP1 Pathway Inhibition.

Aging cell·2025
Same journal

Correction: A method for supervoxel-wise association studies of age and other non-imaging variables from coronary computed tomography angiograms.

Scientific reports·2026
Same journal

Poly(bromophenol blue)/CoSn(OH)<sub>6</sub> cubic particles modified pencil graphite electrode for electrochemical determination of diphenhydramine.

Scientific reports·2026
Same journal

Dietary Chlorella, Spirulina, and acidifier modulate jejunal cytokine-related gene expression in broiler chickens.

Scientific reports·2026
Same journal

Perceived physical activity barriers in university students: associations with fatigue and eating behaviours.

Scientific reports·2026
Same journal

Refuge limitation structures habitat use in agricultural landscapes: evidence from Sunda pangolins.

Scientific reports·2026
Same journal

Lightweight stateless transaction verification with outsourced witness updates for UTXO blockchains.

Scientific reports·2026
See all related articles

Related Experiment Video

Updated: May 26, 2025

Author Spotlight: Advancements in X-ray CT Tool Chain for Tree Core Analysis
06:56

Author Spotlight: Advancements in X-ray CT Tool Chain for Tree Core Analysis

Published on: September 22, 2023

950

An intelligent prediction method for rock core integrity based on deep learning.

Zhaoxia Hu1, Hua Mei1, Lei Yu2

  • 1School of Civil and Architecture Engineering, Hunan Institute of Technology, Hengyang, 421002, China.

Scientific Reports
|February 22, 2025
PubMed
Summary
This summary is machine-generated.

A new deep learning algorithm, Intelligent Detection Algorithm for Rock Core Fissure (IDA-RCF), accurately evaluates rock core integrity. This method automates fissure identification and integrity assessment, improving upon traditional manual evaluations.

Keywords:
Deep learningFissureGeotechnical engineeringIntelligent predictionRock core integrity

More Related Videos

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines
08:27

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

Published on: January 5, 2024

946
Advanced Workflow for Taking High-Quality Increment Cores - New Techniques and Devices
07:40

Advanced Workflow for Taking High-Quality Increment Cores - New Techniques and Devices

Published on: March 10, 2023

2.0K

Related Experiment Videos

Last Updated: May 26, 2025

Author Spotlight: Advancements in X-ray CT Tool Chain for Tree Core Analysis
06:56

Author Spotlight: Advancements in X-ray CT Tool Chain for Tree Core Analysis

Published on: September 22, 2023

950
Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines
08:27

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

Published on: January 5, 2024

946
Advanced Workflow for Taking High-Quality Increment Cores - New Techniques and Devices
07:40

Advanced Workflow for Taking High-Quality Increment Cores - New Techniques and Devices

Published on: March 10, 2023

2.0K

Area of Science:

  • Geotechnical Engineering
  • Artificial Intelligence
  • Computer Vision

Background:

  • Traditional manual evaluation of rock core integrity is inefficient and prone to errors.
  • Accurate assessment of rock core integrity is crucial for geological and civil engineering projects.

Purpose of the Study:

  • To develop a deep learning-based algorithm for automated rock core integrity evaluation.
  • To improve the efficiency and accuracy of rock core fissure identification and integrity assessment.

Main Methods:

  • Proposed IDA-RCF (Intelligent Detection Algorithm for Rock Core Fissure) utilizing a two-branch feature extraction network.
  • Employed Deformable convolution for local fissure features and EfficientViT with self-attention for global context.
  • Implemented a multi-level feature fusion network for adaptive integration of local and global information.

Main Results:

  • IDA-RCF achieved high accuracy with F1 score of 93.09%, mAP@0.5 of 94.44%, and mAP@0.5:0.95 of 84.61%.
  • The algorithm demonstrated a low relative error of 4.38% in fissure rate prediction compared to manual methods.
  • Achieved a prediction accuracy of 93.8% for the degree of rock core integrity.

Conclusions:

  • The proposed IDA-RCF algorithm offers a precise and intelligent solution for evaluating rock core integrity.
  • Automated assessment using IDA-RCF significantly enhances efficiency and reliability over manual methods.
  • This deep learning approach holds promise for advancing rock mechanics and geotechnical engineering applications.