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

Predicting Molecular Geometry02:27

Predicting Molecular Geometry

45.6K
VSEPR Theory for Determination of Electron Pair Geometries
45.6K
Fixed Action Patterns01:06

Fixed Action Patterns

17.6K
A fixed action pattern (FAP) is a specific, hard-wired sequence of behaviors that occurs in response to an external stimulus, called a sign stimulus. The behavior is “fixed” because it is essentially unchangeable—proceeding similarly across individuals of a species every time it occurs.
17.6K
Prediction Intervals01:03

Prediction Intervals

3.3K
The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y. 
3.3K
End Point Prediction: Gran Plot01:07

End Point Prediction: Gran Plot

1.2K
A Gran plot is used to predict the equivalence volume or endpoint of a potentiometric or acid-base titration without reaching the endpoint. Typically, titration data is collected as a function of the titrant's volume up to a point less than the equivalence volume and then transformed into a linear format. The straight line is extended to the x-axis, indicating the necessary titrant volume to achieve the equivalence point.
For potentiometric titration, the Gran plot is created by plotting...
1.2K
Sensitivity, Specificity, and Predicted Value01:13

Sensitivity, Specificity, and Predicted Value

1.2K
In healthcare diagnostics, laboratory tests play a crucial role in identifying and diagnosing a wide range of medical conditions. However, interpreting test results is not always straightforward. An abnormal test result does not always confirm the presence of a disease, just as a normal result does not guarantee its absence. To assess the reliability of these diagnostic tools, healthcare practitioners rely on two key statistical indicators: sensitivity and specificity.
Sensitivity is the...
1.2K
Predicting Reaction Outcomes02:24

Predicting Reaction Outcomes

10.4K
Kinetics describes the rate and path by which a reaction occurs. In contrast, thermodynamics deals with state functions and describes the properties, behavior, and components of a system. It is not concerned with the path taken by the process and cannot address the rate at which a reaction occurs. Although it does provide information about what can happen during a reaction process, it does not describe the detailed steps of what appears on an atomic or a molecular level. On the other hand,...
10.4K

You might also read

Related Articles

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

Sort by
Same author

Ear-Worn Inertial Sensors Can Predict Gait Metrics and Reconstruct Vertical Ground Reaction Force Curves During Running.

Journal of applied biomechanics·2026
Same author

Randomised controlled trial of a very brief nurse-delivered intervention followed by a digital intervention to support medication adherence and reduce blood pressure in people prescribed treatment for hypertension in primary care: protocol for the Programme on Adherence to Medication (PAM) trial.

NIHR open research·2026
Same author

Continuous Mobile Audio Monitoring for Sleep Apnea Detection.

IEEE journal of biomedical and health informatics·2026
Same author

Quantum Chemistry-Driven Molecular Inverse Design of Stable Isomers with Data-Free Reinforcement Learning.

Journal of chemical theory and computation·2026
Same author

SALTS: Streamlined Adaptive Learning for Sensors Time Series.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same author

Deep-Learning Based Segmentation of In-Ear Cardiac Sounds.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025

Related Experiment Video

Updated: Jan 26, 2026

Spatial and Temporal Analysis of Active ERK in the C. elegans Germline
08:40

Spatial and Temporal Analysis of Active ERK in the C. elegans Germline

Published on: November 29, 2016

10.8K

Predicting the temporal activity patterns of new venues.

Krittika D'Silva1, Anastasios Noulas2, Mirco Musolesi3,4

  • 11Department of Computer Science, University of Cambridge, Cambridge, UK.

EPJ Data Science
|April 23, 2019
PubMed
Summary

Predicting new venue popularity is crucial for business success. This study uses mobility data to forecast weekly venue popularity, improving predictions by 41% using temporally similar urban areas.

Keywords:
Human mobility predictionSpatio-temporal patternsUrban computingUrban traffic

More Related Videos

Spatial and Temporal Control of T Cell Activation Using a Photoactivatable Agonist
07:48

Spatial and Temporal Control of T Cell Activation Using a Photoactivatable Agonist

Published on: April 25, 2018

6.6K
Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
10:29

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors

Published on: May 9, 2025

2.2K

Related Experiment Videos

Last Updated: Jan 26, 2026

Spatial and Temporal Analysis of Active ERK in the C. elegans Germline
08:40

Spatial and Temporal Analysis of Active ERK in the C. elegans Germline

Published on: November 29, 2016

10.8K
Spatial and Temporal Control of T Cell Activation Using a Photoactivatable Agonist
07:48

Spatial and Temporal Control of T Cell Activation Using a Photoactivatable Agonist

Published on: April 25, 2018

6.6K
Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
10:29

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors

Published on: May 9, 2025

2.2K

Area of Science:

  • Urban computing
  • Spatio-temporal data analysis
  • Business analytics

Background:

  • Accurate revenue and demand estimation for new venues is vital for initial staffing and resource allocation.
  • Traditional estimation methods rely on coarse-grained local or similar venue data, lacking precision.
  • Crowdsourced mobility data offers enhanced potential for predicting temporal visitation patterns.

Purpose of the Study:

  • To develop a framework for forecasting the weekly popularity of new urban venues.
  • To leverage characteristic temporal signatures and k-nearest neighbor metrics for prediction.
  • To assess the impact of locality and temporal similarity on new venue popularity forecasts.

Main Methods:

  • Utilized Foursquare mobility data, treating venue categories as proxies for urban activities.
  • Developed a prediction framework incorporating temporal signatures and k-nearest neighbor metrics.
  • Evaluated the approach in London, comparing temporally similar areas against random ward selection.

Main Results:

  • Temporally similar urban areas significantly improve new venue visit pattern predictions.
  • Achieved a 41% improvement in prediction accuracy compared to random area selection.
  • Demonstrated the effectiveness of locality and temporal similarity for real-time venue trend prediction.

Conclusions:

  • Mobility data and similarity metrics provide a robust method for forecasting new venue popularity.
  • The framework offers valuable insights for location-based technology design and business owner decisions.
  • Understanding urban activity dynamics through data analysis can optimize new business strategies.