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

Truncation in Survival Analysis01:09

Truncation in Survival Analysis

671
Truncation in survival analysis refers to the exclusion of individuals or events from the dataset based on specific criteria related to the time of the event. This exclusion can happen in two primary forms: left truncation and right truncation.
Left truncation occurs when individuals who experienced the event of interest before a certain time are not included in the study. This is often due to a "delayed entry" into the study where only those who survive until a certain entry point are...
671
Trapezoidal Rule01:26

Trapezoidal Rule

88
Estimating the distance traveled by a vehicle using its recorded velocity over time is a common problem in physics and engineering. When velocity data is available at discrete time intervals, rather than as a continuous function, numerical integration methods such as the trapezoidal rule are often employed to approximate the total displacement.The trapezoidal rule works by dividing the total time interval into several equal segments. Within each segment, the recorded velocities at the endpoints...
88
Cluster Sampling Method01:20

Cluster Sampling Method

15.3K
Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
15.3K
Bootstrapping01:24

Bootstrapping

864
The term "bootstrap" originated in the 19th century as a metaphor for self-improvement or achieving something independently, without external assistance. This concept extends to statistical bootstrapping, a self-contained method for estimating population parameters through resampling, even though it can be computationally intensive. Developed by the American statistician Dr. Bradley Efron in 1979, bootstrapping provides a robust way to perform inference when the original sample size is...
864
Stratified Sampling Method01:16

Stratified Sampling Method

15.9K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a stratified sample, divide the population into groups called strata and then take a...
15.9K
Manipulation and Analysis01:21

Manipulation and Analysis

310
GIS manipulation and analysis functions are vital for decision-making and planning. These activities range from data retrieval tasks, such as selecting information based on specific criteria, to advanced analytical techniques that address complex spatial problems.One critical GIS analysis method is overlaying, which combines multiple data layers to examine impacts. For example, overlaying a river-dammed lake boundary with road networks can identify affected infrastructure. Another common...
310

You might also read

Related Articles

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

Sort by
Same author

The Gyro-Top Optimization: A Physics-inspired Metaheuristic for Engineering Optimization and a Case Study of Feature Selection.

Journal of advanced research·2026
Same author

Multiple-Strategies dung beetle optimizer and its applications in engineering optimization and bankruptcy prediction.

Neural networks : the official journal of the International Neural Network Society·2026
Same author

Bisphenol A promotes esophageal carcinogenesis by activating the MMP1-PCOLCE regulatory axis and remodeling the tumor immune microenvironment.

Naunyn-Schmiedeberg's archives of pharmacology·2026
Same author

The translational roles of circular RNAs in cancers and their underlying molecular mechanisms.

Medical oncology (Northwood, London, England)·2026
Same author

Venetoclax plus Idarubicin and cytarabine as frontline induction for newly diagnosed acute myeloid leukemia in young, fit adults: a real-world study.

Annals of hematology·2026
Same author

Clinicopathological characteristics of alveolar adenoma.

Frontiers in oncology·2026

Related Experiment Video

Updated: Mar 7, 2026

Trajectory Data Analyses for Pedestrian Space-time Activity Study
16:14

Trajectory Data Analyses for Pedestrian Space-time Activity Study

Published on: February 25, 2013

14.3K

A Framework for Bus Trajectory Extraction and Missing Data Recovery for Data Sampled from the Internet.

Changfei Tong1, Huiling Chen2, Qi Xuan3

  • 1College of Physics & Electronic Information Engineering, Wenzhou University, Wenzhou 325035, China. changfei@wzu.edu.cn.

Sensors (Basel, Switzerland)
|February 18, 2017
PubMed
Summary

This study introduces a new framework for extracting bus trajectories and recovering missing data from internet-sourced travel information. The methods improve accuracy in identifying and reconstructing bus routes, enhancing data reliability.

Keywords:
anomaly detectionclusteringmissing data recoverytrajectory processing

More Related Videos

Author Spotlight: A Novel Setup to Conduct Naturalistic Laboratory Experiments with Real Human Actors in Scenarios
07:43

Author Spotlight: A Novel Setup to Conduct Naturalistic Laboratory Experiments with Real Human Actors in Scenarios

Published on: August 4, 2023

2.8K
Using an Automated 3D-tracking System to Record Individual and Shoals of Adult Zebrafish
14:03

Using an Automated 3D-tracking System to Record Individual and Shoals of Adult Zebrafish

Published on: December 5, 2013

11.5K

Related Experiment Videos

Last Updated: Mar 7, 2026

Trajectory Data Analyses for Pedestrian Space-time Activity Study
16:14

Trajectory Data Analyses for Pedestrian Space-time Activity Study

Published on: February 25, 2013

14.3K
Author Spotlight: A Novel Setup to Conduct Naturalistic Laboratory Experiments with Real Human Actors in Scenarios
07:43

Author Spotlight: A Novel Setup to Conduct Naturalistic Laboratory Experiments with Real Human Actors in Scenarios

Published on: August 4, 2023

2.8K
Using an Automated 3D-tracking System to Record Individual and Shoals of Adult Zebrafish
14:03

Using an Automated 3D-tracking System to Record Individual and Shoals of Adult Zebrafish

Published on: December 5, 2013

11.5K

Area of Science:

  • Computer Science
  • Data Science
  • Transportation Engineering

Background:

  • Accurate bus trajectory data is crucial for urban planning and public transit management.
  • Existing methods struggle with incomplete or noisy trajectory data from internet sources.

Purpose of the Study:

  • To develop a robust framework for bus trajectory extraction and missing data recovery.
  • To enhance the accuracy and completeness of bus travel data.

Main Methods:

  • Trajectory extraction involves fuzzy C-means clustering, a novel fuzzy connecting matrix for cleaning, and a connecting algorithm.
  • Missing data recovery utilizes contextual linear interpolation and median value interpolation.

Main Results:

  • The proposed framework effectively extracts and cleans bus trajectories.
  • The methods accurately recover missing data points within and outside trajectories.
  • Experimental results validate the framework's powerful ability in data processing.

Conclusions:

  • The novel framework significantly improves bus trajectory extraction and missing data recovery.
  • This approach offers a reliable solution for processing real-world bus travel data.
  • The findings contribute to more efficient public transportation management through data enhancement.