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

Fixed Action Patterns01:06

Fixed Action Patterns

17.6K
A fixed action pattern (FAP) is a specific, hard-wired sequence of behaviors that occurs in response to an external stimulus, called a sign stimulus. The behavior is “fixed” because it is essentially unchangeable—proceeding similarly across individuals of a species every time it occurs.
17.6K
Gene-Environment Interactions01:20

Gene-Environment Interactions

1.2K
Gene expression is a dynamic process that is significantly influenced by environmental factors. This interaction underlies the complex nature of biological development and the phenotypic differences observed among individuals, even among those with identical genetic makeups. Factors such as radiation, temperature, behavior, nutrition, and stress play pivotal roles in determining how genes are expressed. The concept of the reaction range is central to understanding this interaction. It posits...
1.2K
Patterns of Fever01:26

Patterns of Fever

3.9K
Before understanding the types and patterns of fever, it is essential to know its phases.
3.9K
Background and Environment Affect Phenotype02:27

Background and Environment Affect Phenotype

7.7K
Although the genetic makeup of an organism plays a major role in determining the phenotype, there are also several environmental factors, such as temperature, oxygen availability, presence of mutagens, that can alter an organism’s phenotype.
An example of how genetic background affects phenotype can be seen in horses. The Extension gene in horses is responsible for their coat color. A wild-type gene (EE) produces black pigment in the coat, while a mutant gene (ee) produces red pigment. A...
7.7K
Oxygen Requirements and Growth Patterns01:29

Oxygen Requirements and Growth Patterns

1.6K
Microorganisms exhibit diverse oxygen requirements and growth patterns driven by their metabolic strategies and environmental adaptations. Oxygen, while essential for many organisms, can also be toxic under certain conditions, shaping how microorganisms grow and survive.Oxygen Requirements of MicroorganismsMicroorganisms are classified based on their ability to use or tolerate oxygen:● Obligate aerobes like Mycobacterium tuberculosis need oxygen for energy production, as it serves as the...
1.6K
Transmission-based Precautions II: Airborne and Protective Environment01:25

Transmission-based Precautions II: Airborne and Protective Environment

1.9K
Transmission-based precautions are for patients infected or suspected to be infected (or colonized) with organisms posing a significant risk to others. The transmission precautions include airborne and protective environment precautions.
Airborne precautions:
Use airborne precautions when treating patients known or suspected to have diseases that spread through the air—for example, tuberculosis or measles. These organisms are present in smaller droplets expelled by an infected person and...
1.9K

You might also read

Related Articles

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

Sort by
Same author

Multi-Model Machine Learning for Survival Predictions for Castration-Resistant Prostate Cancer.

Cancers·2026
Same author

RETRACTED: Lee et al. Machine-Learning-Based Survival Prediction in Castration-Resistant Prostate Cancer: A Multi-Model Analysis Using a Comprehensive Clinical Dataset. <i>J. Pers. Med.</i> 2025, <i>15</i>, 432.

Journal of personalized medicine·2026
Same author

RETRACTED: Machine-Learning-Based Survival Prediction in Castration-Resistant Prostate Cancer: A Multi-Model Analysis Using a Comprehensive Clinical Dataset.

Journal of personalized medicine·2025
Same author

Author Correction: Salivary gland organoid culture maintains distinct glandular properties of murine and human major salivary glands.

Nature communications·2024
Same author

Salivary gland organoid culture maintains distinct glandular properties of murine and human major salivary glands.

Nature communications·2022
Same author

Thermoresponsive fiber-based microwells capable of formation and retrieval of salivary gland stem cell spheroids for the regeneration of irradiation-damaged salivary glands.

Journal of tissue engineering·2022
Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026
Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026
Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026
Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026
Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026
Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

Sensors (Basel, Switzerland)·2026
See all related articles

Related Experiment Video

Updated: Feb 2, 2026

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

43.6K

Detecting Incremental Frequent Subgraph Patterns in IoT Environments.

Kyoungsoo Bok1, Jaeyun Jeong2, Dojin Choi3

  • 1Department of Information and Communication Engineering, Chungbuk National University, Chungdae-ro 1, Seowon-Gu, Cheongju, Chungbuk 28644, Korea. ksbok@chungbuk.ac.kr.

Sensors (Basel, Switzerland)
|November 21, 2018
PubMed
Summary
This summary is machine-generated.

This study introduces an efficient method for detecting frequent subgraph patterns in streaming graph data from Internet of Things (IoT) environments. The approach reduces computation by analyzing patterns within sliding windows, improving subgraph pattern discovery.

Keywords:
IoTfrequent pattern detectiongraph streamincrementalsubgraph pattern

More Related Videos

In-vivo Detection of Protein-protein Interactions on Micro-patterned Surfaces
07:42

In-vivo Detection of Protein-protein Interactions on Micro-patterned Surfaces

Published on: March 19, 2010

11.2K
Author Spotlight: Innovative Device Development for Advancing Dendroecology and Wood Anatomy Research
07:05

Author Spotlight: Innovative Device Development for Advancing Dendroecology and Wood Anatomy Research

Published on: September 27, 2024

3.0K

Related Experiment Videos

Last Updated: Feb 2, 2026

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

43.6K
In-vivo Detection of Protein-protein Interactions on Micro-patterned Surfaces
07:42

In-vivo Detection of Protein-protein Interactions on Micro-patterned Surfaces

Published on: March 19, 2010

11.2K
Author Spotlight: Innovative Device Development for Advancing Dendroecology and Wood Anatomy Research
07:05

Author Spotlight: Innovative Device Development for Advancing Dendroecology and Wood Anatomy Research

Published on: September 27, 2024

3.0K

Area of Science:

  • Computer Science
  • Data Science
  • Graph Theory

Background:

  • Graph stream data are increasingly prevalent in Internet of Things (IoT) environments.
  • Detecting and analyzing changes in dynamic graph structures is crucial for understanding complex systems.
  • Existing methods face challenges in efficiently processing continuous graph streams.

Purpose of the Study:

  • To propose an incremental method for detecting frequent subgraph patterns in graph streams.
  • To reduce computational costs associated with analyzing consecutive subgraph patterns.
  • To enhance the meaningfulness of detected patterns by considering edge connectivity.

Main Methods:

  • Utilizing frequent subgraph pattern information from previous sliding windows for incremental detection.
  • Implementing a sliding window mechanism to efficiently track subgraph occurrences.
  • Defining patterns based on connected components via edges to identify meaningful structures.

Main Results:

  • Demonstrated a reduction in computational cost for detecting consecutive subgraph patterns.
  • Successfully identified more meaningful subgraph patterns through edge-based connectivity.
  • Performance evaluations confirmed the superiority of the proposed method.

Conclusions:

  • The proposed incremental method offers an efficient solution for frequent subgraph pattern detection in graph streams.
  • The approach is particularly beneficial for resource-constrained IoT environments.
  • Future work could explore further optimizations and applications of the method.