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

Extraction: Partition and Distribution Coefficients01:14

Extraction: Partition and Distribution Coefficients

4.7K
The distribution law or Nernst's distribution law is the law that governs the distribution of a solute between two immiscible solvents. This law, also known as the partition law, states that if a solute is added to the mixture of two immiscible solvents at a constant temperature, the solute is distributed between the two solvents in such a way that the ratio of solute concentrations in the solvents remains constant at equilibrium.
For extracting a solute from an aqueous phase into an...
4.7K
Analysis of Population Pharmacokinetic Data01:12

Analysis of Population Pharmacokinetic Data

758
Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...
758
pH Scale02:41

pH Scale

80.0K
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...
80.0K
Overview of Microsoft Excel as a Data Analysis Tool01:13

Overview of Microsoft Excel as a Data Analysis Tool

1.6K
Microsoft Excel is a cornerstone tool for data analysis and statistical operations, offering a wide array of functionalities to manage, analyze, and visualize data efficiently. Recognized for its versatility, Excel facilitates the performance of basic to complex statistical operations, serving as an indispensable asset for analysts, researchers, and students alike. Excel's significance in data analysis emanates from its spreadsheet environment, where data can be organized in rows and...
1.6K
Performing a Simple Data Analysis using MS-Excel Function01:17

Performing a Simple Data Analysis using MS-Excel Function

1.1K
Microsoft Excel offers a suite of functions and tools ideal for statistical analysis, making it accessible to students and researchers. This article outlines fundamental Excel functions pivotal for data analysis.
SUM: This function calculates the total sum of a range of values. It's the foundation for aggregating data, essential for determining overall trends and totals in datasets.
AVERAGE: It computes the mean value of a given set of numbers, providing a quick insight into the central...
1.1K
Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

1.6K
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
1.6K

You might also read

Related Articles

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

Sort by
Same author

Oxygen-mediated tandem polyethylene upcycling for selective aromatic synthesis.

National science review·2026
Same author

H3K18 lactylation promotes allergic airway inflammation in asthma via a CSF1/CSF1R/MAPK autocrine axis.

Respiratory research·2026
Same author

Effect of Heat Treatment on the Corrosion and Wear Behavior of Hastelloy C276 Alloy Fabricated via Laser Powder Bed Fusion.

Materials (Basel, Switzerland)·2026
Same author

Shared Central Symptoms but Distinct Age-Specific Patterns in Problematic Short Video Use: Evidence from a Network Analysis Across Early, Middle, and Late Adolescence.

Cyberpsychology, behavior and social networking·2026
Same author

Comparative assessing prefabricated and conventional 3D morphology carbon emission intensity of economy chain hotel buildings in Hangzhou.

Scientific reports·2026
Same author

Usefulness of metabolic score for insulin resistance to predict restenosis after coronary stent implantation.

Annals of medicine·2026
Same journal

MesoSplats: Texture Synthesis with Gaussian Splatting.

IEEE transactions on visualization and computer graphics·2026
Same journal

GLLA: A Unified Force-Directed Graph Layout Framework Supporting Local Adjustments.

IEEE transactions on visualization and computer graphics·2026
Same journal

Multi-Perception Crowd: Learning to combine entity and implicit perception for diverse crowd simulation.

IEEE transactions on visualization and computer graphics·2026
Same journal

Hiding in Plain Sight: Camouflaging Real-world Objects.

IEEE transactions on visualization and computer graphics·2026
Same journal

RTF2Mesh: Restricted Tangent Face Based Mesh Compression With Neural Displacement Fields.

IEEE transactions on visualization and computer graphics·2026
Same journal

Practical Occluder Generation for Mobile Games.

IEEE transactions on visualization and computer graphics·2026
See all related articles

Related Experiment Video

Updated: Feb 6, 2026

Analysis of Multidimensional Microscopy Data Using Cell-ACDC
06:17

Analysis of Multidimensional Microscopy Data Using Cell-ACDC

Published on: November 7, 2025

548

TPFlow: Progressive Partition and Multidimensional Pattern Extraction for Large-Scale Spatio-Temporal Data Analysis.

Dongyu Liu, Panpan Xu, Liu Ren

    IEEE Transactions on Visualization and Computer Graphics
    |August 24, 2018
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a new tensor decomposition algorithm to automatically slice spatio-temporal (ST) data into homogeneous partitions. This method efficiently extracts and summarizes hidden patterns for better data exploration.

    More Related Videos

    Cortical Actin Flow in T Cells Quantified by Spatio-temporal Image Correlation Spectroscopy of Structured Illumination Microscopy Data
    09:09

    Cortical Actin Flow in T Cells Quantified by Spatio-temporal Image Correlation Spectroscopy of Structured Illumination Microscopy Data

    Published on: December 17, 2015

    10.2K
    A Label-free Technique for the Spatio-temporal Imaging of Single Cell Secretions
    09:09

    A Label-free Technique for the Spatio-temporal Imaging of Single Cell Secretions

    Published on: November 23, 2015

    9.1K

    Related Experiment Videos

    Last Updated: Feb 6, 2026

    Analysis of Multidimensional Microscopy Data Using Cell-ACDC
    06:17

    Analysis of Multidimensional Microscopy Data Using Cell-ACDC

    Published on: November 7, 2025

    548
    Cortical Actin Flow in T Cells Quantified by Spatio-temporal Image Correlation Spectroscopy of Structured Illumination Microscopy Data
    09:09

    Cortical Actin Flow in T Cells Quantified by Spatio-temporal Image Correlation Spectroscopy of Structured Illumination Microscopy Data

    Published on: December 17, 2015

    10.2K
    A Label-free Technique for the Spatio-temporal Imaging of Single Cell Secretions
    09:09

    A Label-free Technique for the Spatio-temporal Imaging of Single Cell Secretions

    Published on: November 23, 2015

    9.1K

    Area of Science:

    • Data Science
    • Scientific Visualization
    • Applied Mathematics

    Background:

    • Multidimensional spatio-temporal (ST) datasets require advanced exploration techniques beyond traditional multi-coordinated views.
    • Current methods often fail to guide analysts in identifying hidden patterns within data subsets without prior hypotheses.
    • Manual slicing and pattern searching in large ST datasets is time-consuming and inefficient.

    Purpose of the Study:

    • To develop a novel algorithm for automatic data partitioning and pattern extraction in multidimensional ST data.
    • To introduce a visual analytics framework supporting progressive, level-of-detail exploration of ST data.
    • To enhance the identification and summarization of latent patterns within homogeneous data partitions.

    Main Methods:

    • Modeling multidimensional ST data as tensors.
    • Proposing a piecewise rank-one tensor decomposition algorithm for automatic data slicing.
    • Developing a visual analytics framework for a top-down, progressive partitioning workflow.

    Main Results:

    • The algorithm successfully slices data into homogeneous partitions and extracts latent patterns for comparison.
    • The approach optimizes a quantitative measure of pattern faithfulness in representing original data.
    • Demonstrated effectiveness across diverse applications including sales, customer traffic, and taxi trip analysis.

    Conclusions:

    • The proposed tensor decomposition algorithm and visual analytics framework significantly improve the exploration of multidimensional ST data.
    • The technique enables efficient identification and summarization of hidden patterns, reducing manual effort.
    • Domain expert interviews confirmed the usability and practical value of the developed prototype.