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

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

120
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...
120
Types of Errors: Detection and Minimization01:12

Types of Errors: Detection and Minimization

4.9K
Error is the deviation of the obtained result from the true, expected value or the estimated central value. Errors are expressed in absolute or relative terms.
Absolute error in a measurement is the numerical difference from the true or central value. Relative error is the ratio between absolute error and the true or central value, expressed as a percentage.
Errors can be classified by source, magnitude, and sign. There are three types of errors: systematic, random, and gross.
Systematic or...
4.9K
Estimation of the Physical Quantities01:05

Estimation of the Physical Quantities

6.4K
On many occasions, physicists, other scientists, and engineers need to make estimates of a particular quantity. These are sometimes referred to as guesstimates, order-of-magnitude approximations, back-of-the-envelope calculations, or Fermi calculations. The physicist Enrico Fermi was famous for his ability to estimate various kinds of data with surprising precision. Estimating does not mean guessing a number or a formula at random. Instead, estimation means using prior experience and sound...
6.4K
Errors in Global Positioning System01:26

Errors in Global Positioning System

138
Global Positioning System (GPS) technology has revolutionized navigation and positioning, but its accuracy is often compromised by various errors. These errors, stemming from environmental, satellite, and receiver-related factors, require careful mitigation to ensure reliable performance across applications.Atmospheric ErrorsGPS signals travel through the Earth’s ionosphere and troposphere, introducing delays which affect accuracy. The ionosphere is strongly influenced by charged particles,...
138
Systematic Error: Methodological and Sampling Errors01:15

Systematic Error: Methodological and Sampling Errors

4.4K
In the case of systematic errors, the sources can be identified, and the errors can be subsequently minimized by addressing these sources. According to the source, systematic errors can be divided into sampling, instrumental, methodological, and personal errors.
Sampling errors originate from improper sampling methods or the wrong sample population. These errors can be minimized by refining the sampling strategy. Defective instruments or faulty calibrations are the sources of instrumental...
4.4K
Uncertainty in Measurement: Accuracy and Precision03:37

Uncertainty in Measurement: Accuracy and Precision

96.5K
Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value. 
96.5K

You might also read

Related Articles

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

Sort by
Same author

Ultrasonographic parameters comparison for pre- and postoperative carpal tunnel syndrome release: A single-center prospective study.

Medicine·2026
Same author

Biofilm- and Spore-Disruptive Star-Shaped Poly(l-lysine)/Hyaluronic Acid Microgels for Targeted Oral Therapy of <i>Clostridioides difficile</i> Infection.

Biomacromolecules·2026
Same author

Surgical techniques for thoracoscopic secondary carinal reconstruction with stepwise barbed sutures.

General thoracic and cardiovascular surgery·2026
Same author

Identification of MicroRNAs Involved in Different Layers of Rice-Magnaporthe oryzae Interaction.

Rice (New York, N.Y.)·2025
Same author

circHIPK2 promotes malignant progression of laryngeal squamous cell carcinoma through the miR-889-3p/MCTS1/IL-6 axis.

Translational oncology·2025
Same author

Emerging roles of the acid sphingomyelinase/ceramide pathway in metabolic and cardiovascular diseases: Mechanistic insights and therapeutic implications.

World journal of cardiology·2025
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: Oct 13, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

731

Optimization-Based Approaches for Minimizing Deployment Costs for Wireless Sensor Networks with Bounded Estimation

Chiu-Han Hsiao1, Frank Yeong-Sung Lin2, Hao-Jyun Yang1

  • 1Research Center for Information Technology Innovation, Academia Sinica, Taipei 115, Taiwan.

Sensors (Basel, Switzerland)
|November 13, 2021
PubMed
Summary
This summary is machine-generated.

This study optimizes wireless sensor networks (WSN) deployment by minimizing costs and maintaining accuracy. Correlation-aware methods reduce sensors while ensuring data integrity and extending network lifetime.

Keywords:
Lagrangian RelaxationXGBoostnetwork deploymentpearson correlationwireless sensor networks (WSNs)

More Related Videos

Effective Analysis of Human Exposure Conditions with Body-worn Dosimeters in the 2.4 GHz Band
06:43

Effective Analysis of Human Exposure Conditions with Body-worn Dosimeters in the 2.4 GHz Band

Published on: May 2, 2018

7.2K
Design and Analysis for Fall Detection System Simplification
08:05

Design and Analysis for Fall Detection System Simplification

Published on: April 6, 2020

10.9K

Related Experiment Videos

Last Updated: Oct 13, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

731
Effective Analysis of Human Exposure Conditions with Body-worn Dosimeters in the 2.4 GHz Band
06:43

Effective Analysis of Human Exposure Conditions with Body-worn Dosimeters in the 2.4 GHz Band

Published on: May 2, 2018

7.2K
Design and Analysis for Fall Detection System Simplification
08:05

Design and Analysis for Fall Detection System Simplification

Published on: April 6, 2020

10.9K

Area of Science:

  • Computer Science
  • Electrical Engineering
  • Network Engineering

Background:

  • Wireless sensor networks (WSN) are increasingly common, generating vast amounts of data.
  • Cost and energy constraints necessitate sensor reduction strategies.
  • Maintaining data accuracy within acceptable error tolerances is crucial.

Purpose of the Study:

  • To develop an optimization-based approach for sensor deployment in WSN.
  • To minimize deployment costs while adhering to error thresholds.
  • To enhance the accuracy and longevity of WSN.

Main Methods:

  • A correlation-aware mathematical model combining theoretical and practical aspects.
  • Sensor deployment strategies utilizing XGBoost, Pearson correlation, and Lagrangian Relaxation (LR).
  • Minimizing sensor count and deployment expenses.

Main Results:

  • Achieved significant cost reduction in sensor deployment.
  • Maintained estimation errors below a predefined threshold.
  • Ensured high accuracy of gathered data and extended WSN operational lifetime.

Conclusions:

  • The proposed correlation-aware method effectively balances cost, accuracy, and WSN lifetime.
  • The approach is adaptable for sensor distribution challenges across diverse applications.
  • Optimization strategies like LR are vital for efficient WSN management.