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

Data: Types and Distribution01:19

Data: Types and Distribution

1.5K
In biostatistics, data are the observations collected for analysis. There are two main types: parametric and non-parametric. Parametric data, which include continuous (e.g., weight) and discrete numerical data (e.g., number of tablets), assume a particular distribution pattern, often the normal distribution. Non-parametric data do not adhere to a specific distribution and typically comprise nominal (e.g., gender) and ordinal categorical data (e.g., pain scale ratings).
Distributions in...
1.5K
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

244
Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
244
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

910
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
910
Statistical Methods to Analyze Parametric Data: ANOVA01:12

Statistical Methods to Analyze Parametric Data: ANOVA

1.6K
Analysis of Variance, or ANOVA, is a powerful statistical technique used to analyze parametric data, primarily in research and experimental studies. It's designed to compare the means of two or more groups, assisting researchers in identifying any significant differences between these group means. There are two main types of ANOVA based on the complexity of the analysis: one-way and two-way.
One-way ANOVA is applied when a single independent variable or factor is scrutinized. It compares...
1.6K
Drug Distribution: Volume of Distribution01:25

Drug Distribution: Volume of Distribution

7.3K
The volume of distribution refers to the theoretical volume necessary to contain the entire amount of an administered drug at the same concentration observed in the blood plasma. The body's intracellular fluid compartment, which makes up two-thirds of the total body water, is contrasted with the extracellular fluid compartment—comprising plasma and interstitial fluid—that accounts for one-third. The volume of distribution can vary depending on the characteristics of the drug.
7.3K
F Distribution01:19

F Distribution

9.0K
The F distribution was named after Sir Ronald Fisher, an English statistician. The F statistic is a ratio (a fraction) with two sets of degrees of freedom; one for the numerator and one for the denominator. The F distribution is derived from the Student's t distribution. The values of the F distribution are squares of the corresponding values of the t distribution. One-Way ANOVA expands the t test for comparing more than two groups. The scope of that derivation is beyond the level of this...
9.0K

You might also read

Related Articles

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

Sort by
Same author

A two-stage deep learning-based hybrid model for daily wind speed forecasting.

Heliyon·2025
Same author

Coronary Artery Disease Diagnosis; Ranking the Significant Features Using a Random Trees Model.

International journal of environmental research and public health·2020
Same author

Integrated machine learning methods with resampling algorithms for flood susceptibility prediction.

The Science of the total environment·2019
Same author

Flash-flood hazard assessment using ensembles and Bayesian-based machine learning models: Application of the simulated annealing feature selection method.

The Science of the total environment·2019
Same author

Spatial hazard assessment of the PM10 using machine learning models in Barcelona, Spain.

The Science of the total environment·2019
Same author

Securing IoT-Based RFID Systems: A Robust Authentication Protocol Using Symmetric Cryptography.

Sensors (Basel, Switzerland)·2019
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: Jan 22, 2026

Methods to Study Changes in Inherent Protein Aggregation with Age in Caenorhabditis elegans
11:57

Methods to Study Changes in Inherent Protein Aggregation with Age in Caenorhabditis elegans

Published on: November 26, 2017

9.1K

An Enhanced Distributed Data Aggregation Method in the Internet of Things.

Mohammad Hossein Homaei1, Ely Salwana2, Shahaboddin Shamshirband3,4

  • 1Internet of Things Laboratory of Iran (Gloriot), Hamedan, Iran.

Sensors (Basel, Switzerland)
|July 21, 2019
PubMed
Summary
This summary is machine-generated.

This study introduces a novel Learning Automata-based Routing Protocol for Low-Power and Lossy Networks (LA-RPL) to address Internet of Things (IoT) challenges. LA-RPL enhances data aggregation and transmission, improving network efficiency and reducing congestion.

Keywords:
Internet of Thing (IoT)RPLdata aggregation methodslearning automatarouting

More Related Videos

Stress Distribution During Cold Compression of Rocks and Mineral Aggregates Using Synchrotron-based X-Ray Diffraction
10:36

Stress Distribution During Cold Compression of Rocks and Mineral Aggregates Using Synchrotron-based X-Ray Diffraction

Published on: May 20, 2018

10.1K
An Efficient and Flexible Cell Aggregation Method for 3D Spheroid Production
07:46

An Efficient and Flexible Cell Aggregation Method for 3D Spheroid Production

Published on: March 27, 2017

25.4K

Related Experiment Videos

Last Updated: Jan 22, 2026

Methods to Study Changes in Inherent Protein Aggregation with Age in Caenorhabditis elegans
11:57

Methods to Study Changes in Inherent Protein Aggregation with Age in Caenorhabditis elegans

Published on: November 26, 2017

9.1K
Stress Distribution During Cold Compression of Rocks and Mineral Aggregates Using Synchrotron-based X-Ray Diffraction
10:36

Stress Distribution During Cold Compression of Rocks and Mineral Aggregates Using Synchrotron-based X-Ray Diffraction

Published on: May 20, 2018

10.1K
An Efficient and Flexible Cell Aggregation Method for 3D Spheroid Production
07:46

An Efficient and Flexible Cell Aggregation Method for 3D Spheroid Production

Published on: March 27, 2017

25.4K

Area of Science:

  • Computer Science
  • Network Engineering
  • Wireless Communication

Background:

  • The Internet of Things (IoT) faces significant challenges due to limited node resources and unstable communication.
  • These limitations impact data aggregation, transmission efficiency, and overall routing performance in IoT networks.
  • Intelligent approaches are needed to overcome reduced availability times and unstable node communications.

Purpose of the Study:

  • To propose a distributed method for balancing child nodes and reducing network congestion in IoT.
  • To introduce a dynamic data aggregation approach using Learning Automata for the Routing Protocol for Low-Power and Lossy Networks (LA-RPL).
  • To enhance the efficiency of IoT networks concerning energy consumption, control overhead, delay, packet loss, and aggregation rates.

Main Methods:

  • A distributed method was developed to balance child nodes by restricting node degree, thereby increasing network graph height and reducing congestion.
  • A dynamic data aggregation strategy was implemented using Learning Automata integrated into each node for data aggregation and transmission.
  • The proposed LA-RPL protocol was evaluated through simulations and experimental results.

Main Results:

  • The LA-RPL protocol demonstrated superior performance compared to existing methods.
  • Significant improvements were observed in energy consumption and network control overhead.
  • Enhanced aggregation rates and reduced end-to-end delay and packet loss were achieved.

Conclusions:

  • The proposed LA-RPL effectively addresses key challenges in Low-Power and Lossy Networks.
  • Learning Automata integration provides a robust solution for dynamic data aggregation and efficient routing in IoT.
  • LA-RPL offers a promising approach for optimizing IoT network performance and resource utilization.