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

Random Error01:04

Random Error

7.5K
Random or indeterminate errors originate from various uncontrollable variables, such as variations in environmental conditions, instrument imperfections, or the inherent variability of the phenomena being measured. Usually, these errors cannot be predicted, estimated, or characterized because their direction and magnitude often vary in magnitude and direction even during consecutive measurements. As a result, they are difficult to eliminate. However, the aggregate effect of these errors can be...
7.5K
Random and Systematic Errors01:20

Random and Systematic Errors

14.2K
Scientists always try their best to record measurements with the utmost accuracy and precision. However, sometimes errors do occur. These errors can be random or systematic. Random errors are observed due to the inconsistency or fluctuation in the measurement process, or variations in the quantity itself that is being measured. Such errors fluctuate from being greater than or less than the true value in repeated measurements. Consider a scientist measuring the length of an earthworm using a...
14.2K
Common Leveling Mistakes and Errors01:17

Common Leveling Mistakes and Errors

297
A survey team is tasked with determining the elevation difference between points Point A and Point B, separated by uneven terrain. They use a leveling instrument and a leveling rod.Common MistakesMisreading the Rod: During a backsight reading at Point A, the instrumentman observes the rod partially obscured by tall grass. Instead of reading 1.135 m, they mistakenly record 1.735 m due to the misalignment of the crosshair with the wrong graduation. This error adds 0.600 m to all subsequent...
297
Accuracy, limits, and approximation01:28

Accuracy, limits, and approximation

1.0K
Accuracy, limits, and approximations are common in many fields, especially in engineering calculations. These concepts are imperative for ensuring that a given value is as close as possible to its true value.
Accuracy is defined as the closeness of the measured value to the true or actual value. In engineering mechanics, repeated measurements are taken during theoretical or experimental analyses to ensure that the result is precise and accurate.
The accuracy of any solution is based on the...
1.0K
Types of Errors: Detection and Minimization01:12

Types of Errors: Detection and Minimization

9.2K
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...
9.2K
Effects of EDTA on End-Point Detection Methods01:18

Effects of EDTA on End-Point Detection Methods

560
Different methods, such as visual observance of metal-ion indicators, spectroscopic techniques, and potentiometric methods, can determine the endpoint of an EDTA titration.
In the visual method, metal-ion indicators (metallochromic dyes), which have distinct colors in their free and complex forms, are added to the mixture to signal the titration's end point. They form stable complexes with metal ions, but these complexes are weaker than the corresponding metal–EDTA complexes. As a...
560

You might also read

Related Articles

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

Sort by
Same author

Drug-Conjugated Tam-NHC-Gold(I) Complexes Overcome <i>ESR1</i> Mutant Breast Cancer Resistance and Downregulate the RAMP3/CALCR Signaling Pathway.

Journal of medicinal chemistry·2026
Same author

Hepatitis C virus inhibits the E2F2/PI3K/AKT signaling pathway through miR-378b and leads to glycolipid metabolism disorders in the liver.

Molecular biology reports·2026
Same author

Learning Occlusion-Dynamic Invariant Representations for Multi-Object Tracking.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same author

Designer Dynamic DNA Nanoaggregate in Living Cell for Mitochondrial Energy Restriction.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026
Same author

Discovery of NTQ2494, a potent and orally bioavailable inhibitor of AXL kinase for the treatment of human tumors.

European journal of medicinal chemistry·2026
Same author

Data-Driven Interrogation of Reactivity in Acid-Catalyzed Carbonyl-Olefin Metathesis with Machine Learning and Large Language Models.

Journal of the American Chemical Society·2026
Same journal

An Evolutionary Algorithm Assisted by an Ensemble of Pareto-Optimal Surrogate Models.

IEEE transactions on cybernetics·2026
Same journal

A Quantum Self-Attention Neural Network Model on Quantum Circuits.

IEEE transactions on cybernetics·2026
Same journal

Semi-Explicit Solution of Some Discrete-Time Higher-Order-Cost Mean-Field-Type Control.

IEEE transactions on cybernetics·2026
Same journal

A Novel One-Step Small Object Detector for Autonomous Aerial Vehicles.

IEEE transactions on cybernetics·2026
Same journal

Online Data-Driven-Based Optimal Output Tracking Control Without Initial Stabilizing Policy.

IEEE transactions on cybernetics·2026
Same journal

Digital Redesign-Based Interval State Estimation for Continuous Systems With Aperiodic Discrete Measurements.

IEEE transactions on cybernetics·2026
See all related articles

Related Experiment Video

Updated: Dec 23, 2025

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
06:45

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Published on: October 28, 2022

2.0K

False-Data-Injection Attacks on Remote Distributed Consensus Estimation.

Hao Liu, Ben Niu, Yuzhe Li

    IEEE Transactions on Cybernetics
    |April 21, 2020
    PubMed
    Summary
    This summary is machine-generated.

    This study addresses security in remote distributed consensus estimation. It analyzes stealthy false-data attacks on wireless sensor networks, using relative entropy to detect intrusions and maximize performance degradation.

    Related Experiment Videos

    Last Updated: Dec 23, 2025

    Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
    06:45

    Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

    Published on: October 28, 2022

    2.0K

    Area of Science:

    • Control Systems and Signal Processing
    • Cybersecurity in Networked Systems

    Background:

    • Remote distributed consensus estimation relies on secure wireless sensor networks.
    • Attacks on data transmission can compromise estimation accuracy and system integrity.

    Purpose of the Study:

    • To investigate security vulnerabilities in remote distributed consensus estimation over wireless networks.
    • To develop methods for detecting stealthy false-data attacks.
    • To analyze the impact of such attacks on system performance.

    Main Methods:

    • Utilizing relative entropy as a metric for attack stealthiness.
    • Analyzing performance degradation caused by undetected attacks.
    • Characterizing false-data attack strategies to maximize integrated mean-square error (IMSE).

    Main Results:

    • Relative entropy effectively quantifies the stealthiness of data attacks.
    • A specific false-data attack strategy is identified that maximizes IMSE.
    • The study quantifies the trade-off between attack stealthiness and performance degradation.

    Conclusions:

    • Understanding and quantifying stealthy attacks is crucial for securing distributed estimation systems.
    • The proposed methods provide a framework for evaluating system resilience against sophisticated cyber threats.
    • Balancing attack impact and stealth is a key consideration in network security design.