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

Protein Networks02:26

Protein Networks

4.5K
An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
4.5K
Protein Networks02:26

Protein Networks

2.9K
2.9K
pH Scale02:41

pH Scale

79.7K
Hydronium and hydroxide ions are present both in pure water and in all aqueous solutions, and their concentrations are inversely proportional as determined by the ion product of water (Kw). The concentrations of these ions in a solution are often critical determinants of the solution’s properties and the chemical behaviors of its other solutes. Two different solutions can differ in their hydronium or hydroxide ion concentrations by a million, billion, or even trillion times. A common means of...
79.7K
Network Covalent Solids02:18

Network Covalent Solids

16.2K
Network covalent solids contain a three-dimensional network of covalently bonded atoms as found in the crystal structures of nonmetals like diamond, graphite, silicon, and some covalent compounds, such as silicon dioxide (sand) and silicon carbide (carborundum, the abrasive on sandpaper). Many minerals have networks of covalent bonds.
To break or to melt a covalent network solid, covalent bonds must be broken. Because covalent bonds are relatively strong, covalent network solids are typically...
16.2K
Scaling01:26

Scaling

593
In designing and analyzing filters, resonant circuits, or circuit analysis at large, working with standard element values like 1 ohm, 1 henry, or 1 farad can be convenient before scaling these values to more realistic figures. This approach is widely utilized by not employing realistic element values in numerous examples and problems; it simplifies mastering circuit analysis through convenient component values. The complexity of calculations is thereby reduced, with the understanding that...
593
What is Natural Selection?01:32

What is Natural Selection?

129.1K
Natural selection is an evolutionary process in which individuals with survival-promoting traits reproduce at higher rates. These favorable traits become more common within a population or species. Naturally selected traits initially arise via random genetic mutations. In order for selection to occur, there must be variation within a population, the trait controlling the variation must be heritable, and there must be an evolutionary advantage for variation in the trait.
129.1K

You might also read

Related Articles

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

Sort by
Same author

Establishing a high sensitivity detection method for SARS-CoV-2 IgM/IgG and developing a clinical application of this method.

Emerging microbes & infections·2020
Same author

Reactivity of aromatic contaminants towards nitrate radical in tropospheric gas and aqueous phase.

Journal of hazardous materials·2020
Same author

Dysregulated adaptive immune response contributes to severe COVID-19.

Cell research·2020
Same author

Theoretical investigation on the contribution of HO, SO<sub>4</sub><sup>-</sup> and CO<sub>3</sub><sup>-</sup> radicals to the degradation of phenacetin in water: Mechanisms, kinetics, and toxicity evaluation.

Ecotoxicology and environmental safety·2020
Same author

Identification of Sulfenylated Cysteines in <i>Arabidopsis thaliana</i> Proteins Using a Disulfide-Linked Peptide Reporter.

Frontiers in plant science·2020
Same author

A feasibility study of individual 3D-printed navigation template for the deep external fixator pin position on the iliac crest.

BMC musculoskeletal disorders·2020
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

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

1.2K

Sensor Selection for Decentralized Large-Scale Multi-Target Tracking Network.

Feng Lian1, Liming Hou2, Bo Wei3

  • 1Ministry of Education Key Laboratory for Intelligent Networks and Network Security (MOE KLINNS), School of Electronics and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, China. lianfeng1981@xjtu.edu.cn.

Sensors (Basel, Switzerland)
|November 28, 2018
PubMed
Summary
This summary is machine-generated.

This study introduces an optimized sensor selection algorithm for decentralized multi-target tracking (MTT) using labeled random finite sets (RFS). The novel approach enhances tracking accuracy and efficiency in complex networks.

Keywords:
decentralized sensor networkerror boundlabeled random finite setmulti-target trackingsensor selection

More Related Videos

Multi-target Parallel Processing Approach for Gene-to-structure Determination of the Influenza Polymerase PB2 Subunit
22:10

Multi-target Parallel Processing Approach for Gene-to-structure Determination of the Influenza Polymerase PB2 Subunit

Published on: June 28, 2013

13.7K
Fabricating Multi-Component Lipid Nanotube Networks Using the Gliding Kinesin Motility Assay
05:16

Fabricating Multi-Component Lipid Nanotube Networks Using the Gliding Kinesin Motility Assay

Published on: July 26, 2021

2.0K

Related Experiment Videos

Last Updated: Feb 2, 2026

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

1.2K
Multi-target Parallel Processing Approach for Gene-to-structure Determination of the Influenza Polymerase PB2 Subunit
22:10

Multi-target Parallel Processing Approach for Gene-to-structure Determination of the Influenza Polymerase PB2 Subunit

Published on: June 28, 2013

13.7K
Fabricating Multi-Component Lipid Nanotube Networks Using the Gliding Kinesin Motility Assay
05:16

Fabricating Multi-Component Lipid Nanotube Networks Using the Gliding Kinesin Motility Assay

Published on: July 26, 2021

2.0K

Area of Science:

  • Robotics and Control Systems
  • Signal Processing
  • Information Theory

Background:

  • Decentralized large-scale multi-target tracking (MTT) networks face challenges in sensor selection and data fusion.
  • Labeled random finite set (RFS) frameworks offer a probabilistic approach to handling uncertainties in MTT.
  • Existing methods for sensor selection and density fusion in RFS-based MTT require improvement for efficiency and accuracy.

Purpose of the Study:

  • To propose a novel optimization algorithm for sensor selection in decentralized large-scale MTT networks.
  • To develop a new metric, the label assignment (LA) metric, for evaluating labeled sets in RFS frameworks.
  • To establish a lower bound for mean square error using the LA metric as an objective function for sensor selection.

Main Methods:

  • The study utilizes a marginalized δ-generalized labeled multi-Bernoulli RFS.
  • Weighted Kullback-Leibler average (KLA) is employed for fusing local multi-target densities.
  • An information inequality is used to derive the lower bound of the LA metric-based mean square error for sensor selection optimization.
  • Sequential Monte Carlo and Gaussian mixture implementations are presented for the derived bound.
  • A coordinate descent method is proposed to balance computational cost and MTT accuracy.

Main Results:

  • A new sensor selection optimization algorithm is proposed for RFS-based decentralized MTT.
  • The label assignment (LA) metric is introduced to quantify distances between labeled sets.
  • A lower bound for mean square error is derived, serving as the objective for sensor selection.
  • The derived bound also provides a basis for setting KLA weights.
  • Simulations demonstrate the effectiveness of the proposed method across various signal-to-noise ratio scenarios.

Conclusions:

  • The proposed sensor selection algorithm effectively optimizes decentralized large-scale MTT networks within the labeled RFS framework.
  • The LA metric and its derived lower bound offer a principled approach to sensor selection and performance evaluation.
  • The coordinate descent method provides a practical solution for computational efficiency in sensor selection.
  • The method shows robust performance under different noise conditions, validating its practical applicability.