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

Outliers and Influential Points01:08

Outliers and Influential Points

6.8K
An outlier is an observation of data that does not fit the rest of the data. It is sometimes called an extreme value. When you graph an outlier, it will appear not to fit the pattern of the graph. Some outliers are due to mistakes (for example, writing down 50 instead of 500), while others may indicate that something unusual is happening. Outliers are present far from the least squares line in the vertical direction. They have large "errors," where the "error" or residual is the...
6.8K
What Are Outliers?01:12

What Are Outliers?

5.7K
Outliers are observed data points that are far from the least squares line. They have unusual values and need to be examined carefully. Though an outlier may result from erroneous data, at other times, it may hold valuable information about the population under study and should be included in the data. Hence, it is crucial to examine what causes a data point to be an outlier.
The z score is used to find outliers or unusual values. It should be noted that any values beyond -2 and +2 are...
5.7K
Quantifying and Rejecting Outliers: The Grubbs Test01:02

Quantifying and Rejecting Outliers: The Grubbs Test

5.0K
Sometimes, a data set can have a recorded numerical observation that greatly  deviates from the rest of the data. Assuming that the data is normally distributed, a statistical method called the Grubbs test can be used to determine whether the observation is truly an outlier.  To perform a two-tailed Grubbs test, first, calculate the absolute difference between the outlier and the mean. Then, calculate the ratio between this difference and the standard deviation of the sample. This...
5.0K
Detection of Gross Error: The Q Test01:00

Detection of Gross Error: The Q Test

8.1K
When one or more data points appear far from the rest of the data, there is a need to determine whether they are outliers and whether they should be eliminated from the data set to ensure an accurate representation of the measured value. In many cases, outliers arise from gross errors (or human errors) and do not accurately reflect the underlying phenomenon. In some cases, however, these apparent outliers reflect true phenomenological differences. In these cases, we can use statistical methods...
8.1K
Local Attraction01:22

Local Attraction

497
Local attraction refers to disturbances in compass readings caused by magnetic influences from nearby objects such as metal fences, buried pipes, vehicles, buildings, power lines, or natural iron ore deposits. Small items like wristwatches, steel tools, or belt buckles can also interfere with the compass by creating local magnetic fields that distort the Earth's natural magnetic field. These distortions lead to inaccurate readings, posing navigation and land surveying challenges.Local...
497
Design Example: Identifying the Locations of Monuments in the Field Using Global Positioning System Device01:30

Design Example: Identifying the Locations of Monuments in the Field Using Global Positioning System Device

491
Surveyors use Global Positioning System (GPS) technology to measure the precise location and elevation of points on Earth. In a recent survey, GPS receivers were used to determine the coordinates and elevations of two park monuments. The process involved careful mission planning, data collection, and correction to ensure accuracy. The survey began with mission planning to identify optimal satellite visibility and minimize Position Dilution of Precision (PDOP). A geodetic control point...
491

You might also read

Related Articles

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

Sort by
Same author

Factors affecting the gut microbiota of rural residents under different physical activity levels: a cross-sectional study.

Frontiers in microbiology·2026
Same author

GPR161 contributes to macrophage glycolytic reprogramming via targeting C5aR1 in acute lung injury.

Cellular & molecular biology letters·2026
Same author

Dual-tuning of morphology and coordination in single-atom catalysts via organic linker engineering for singlet oxygen-dominated Fenton-like reactions.

Journal of hazardous materials·2026
Same author

Mechanistic insights into Cd resilience enhancement by molybdenum trioxide nanoparticles in Solanum nigrum L.: Distinct molecular regulation from Mo<sup>6+</sup> through multi-omics perspective.

Journal of environmental sciences (China)·2026
Same author

A telomere-to-telomere gap-free genome of the new cultivar 'Zhongtian No. 5', combined with pan-genome analysis, aids in exploration and genetic enhancement of red clover (<i>Trifolium pratense</i> L.).

Horticulture research·2026
Same author

Global, regional, and national burdens of contact dermatitis: A longitudinal analysis from the Global Burden of Disease Study, 1990∼2021.

Journal of the American Academy of Dermatology·2026
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: Apr 15, 2026

A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions
07:34

A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions

Published on: March 25, 2014

10.4K

Nonlinear optimization-based device-free localization with outlier link rejection.

Wendong Xiao1, Biao Song2, Xiting Yu3

  • 1School of Automation & Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China. wdxiao@ustb.edu.cn.

Sensors (Basel, Switzerland)
|April 9, 2015
PubMed
Summary
This summary is machine-generated.

This study introduces a new method for device-free localization (DFL) that accurately estimates locations by rejecting unreliable wireless signals. The novel nonlinear optimization approach with outlier link rejection (NOOLR) improves accuracy in smart city applications.

More Related Videos

An Automated System for Sound Localization Testing in Hearing-Impaired Listeners
07:56

An Automated System for Sound Localization Testing in Hearing-Impaired Listeners

Published on: March 13, 2026

144

Related Experiment Videos

Last Updated: Apr 15, 2026

A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions
07:34

A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions

Published on: March 25, 2014

10.4K
An Automated System for Sound Localization Testing in Hearing-Impaired Listeners
07:56

An Automated System for Sound Localization Testing in Hearing-Impaired Listeners

Published on: March 13, 2026

144

Area of Science:

  • Wireless communication
  • Localization techniques
  • Signal processing

Background:

  • Device-free localization (DFL) enables tracking targets without electronic devices, crucial for smart cities.
  • Existing Received Signal Strength (RSS)-based DFL methods struggle with wireless channel uncertainties and erroneous link data.
  • Radio Tomographic Imaging (RTI) is a common but potentially inaccurate DFL approach.

Purpose of the Study:

  • To propose a robust and accurate RSS-based device-free localization (DFL) method.
  • To address the challenge of signal pollution and erroneous data in wireless links for DFL.
  • To enhance localization accuracy in smart city applications through improved DFL.

Main Methods:

  • Developed a novel nonlinear optimization approach with outlier link rejection (NOOLR).
  • Implemented three key strategies: differential RSS detection for affected link identification, geometrical analysis for outlier link rejection, and nonlinear optimization for location estimation.
  • Compared the proposed NOOLR method against the existing Radio Tomographic Imaging (RTI) approach.

Main Results:

  • The NOOLR approach demonstrated robustness against wireless signal fluctuations.
  • NOOLR achieved superior localization accuracy compared to the RTI method.
  • Experimental results validated the effectiveness of the proposed outlier rejection and nonlinear optimization strategies.

Conclusions:

  • The proposed NOOLR method offers a significant improvement in accuracy and robustness for RSS-based DFL.
  • NOOLR effectively handles unreliable wireless links, leading to more dependable localization.
  • This technique has strong potential for enhancing smart city applications relying on precise device-free localization.