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

Types of Errors: Detection and Minimization01:12

Types of Errors: Detection and Minimization

11.3K
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...
11.3K
Induced-fit Model01:13

Induced-fit Model

89.1K
Most chemical reactions in cells require enzymes—biological catalysts that speed up the reaction without being consumed or permanently changed. They reduce the activation energy needed to convert the reactants into products. Enzymes are proteins, that usually work by binding to a substrate—a reactant molecule that they act upon.
Enzymes exhibit substrate specificity, meaning that they can only bind to certain substrates. This is mainly determined by the shape and chemical...
89.1K
Inclusive Fitness00:57

Inclusive Fitness

39.6K
Most altruistic behavior—in which one animal helps another at a cost to themselves—occurs between relatives. Scientists think these altruistic behaviors evolved because they increase the inclusive fitness of the animal providing help.
39.6K
Goodness-of-Fit Test01:16

Goodness-of-Fit Test

9.2K
The goodness-of-fit test is a type of hypothesis test which determines whether the data "fits" a particular distribution. For example, one may suspect that some anonymous data may fit a binomial distribution. A chi-square test (meaning the distribution for the hypothesis test is chi-square) can be used to determine if there is a fit. The null and alternative hypotheses may be written in sentences or stated as equations or inequalities. The test statistic for a goodness-of-fit test is given as...
9.2K
Formulation and Manufacturing Process: Physical Attributes of Generic Tablets and Capsules01:18

Formulation and Manufacturing Process: Physical Attributes of Generic Tablets and Capsules

320
Bioequivalence in generic drugs, such as tablets and capsules, refers to their pharmaceutical equivalence to the brand-name counterparts. However, for therapeutic equivalence, manufacturers must also consider physical attributes like size, shape, and weight (FDA Guidance for Industry, December 2003). Discrepancies in these aspects could impact patient compliance and cause medication errors. For instance, swallowing difficulties, often experienced with larger tablets or capsules, can lead to...
320
Expected Frequencies in Goodness-of-Fit Tests01:19

Expected Frequencies in Goodness-of-Fit Tests

8.7K
A goodness-of-fit test is conducted to determine whether the observed frequency values are statistically similar to the frequencies expected for the dataset. Suppose the expected frequencies for a dataset are equal such as when predicting the frequency of any number appearing when casting a die. In that case, the expected frequency is the ratio of the total number of observations (n)  to the number of categories (k).
8.7K

You might also read

Related Articles

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

Sort by
Same author

Erratum for: Associations of MRI-derived Paraspinal IMAT and LMM with Cardiometabolic Risk Factors: Results from a German Cohort.

Radiology·2026
Same author

DynSUP: Dynamic Gaussian Splatting From an Unposed Image Pair.

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

ProtoFlow: interpretable and robust surgical workflow modeling with learned dynamic scene graph prototypes.

International journal of computer assisted radiology and surgery·2026
Same author

Toward comprehensive real-time scene understanding in ophthalmic surgery through multimodal image fusion.

International journal of computer assisted radiology and surgery·2026
Same author

DefSynUS: Real-time patient-specific intrahepatic vessel identification via deformation-aware CT-US domain adaptation.

International journal of computer assisted radiology and surgery·2026
Same author

Smartphone photogrammetry for rapid 3D surface modeling of head and neck specimens to support frozen section communication: A feasibility pilot study.

Oral oncology·2026

Related Experiment Video

Updated: Jan 28, 2026

Directed Differentiation of Primitive and Definitive Hematopoietic Progenitors from Human Pluripotent Stem Cells
14:37

Directed Differentiation of Primitive and Definitive Hematopoietic Progenitors from Human Pluripotent Stem Cells

Published on: November 1, 2017

11.8K

Generic Primitive Detection in Point Clouds Using Novel Minimal Quadric Fits.

Tolga Birdal, Benjamin Busam, Nassir Navab

    IEEE Transactions on Pattern Analysis and Machine Intelligence
    |February 23, 2019
    PubMed
    Summary

    This study introduces a new method for detecting 3D shapes like planes and spheres in complex point clouds. It efficiently identifies multiple object types without prior segmentation, improving 3D scene understanding.

    More Related Videos

    Generic Protocol for Optimization of Heterologous Protein Production Using Automated Microbioreactor Technology
    06:24

    Generic Protocol for Optimization of Heterologous Protein Production Using Automated Microbioreactor Technology

    Published on: December 15, 2017

    10.7K
    A Quantitative Fitness Analysis Workflow
    11:39

    A Quantitative Fitness Analysis Workflow

    Published on: August 13, 2012

    14.9K

    Related Experiment Videos

    Last Updated: Jan 28, 2026

    Directed Differentiation of Primitive and Definitive Hematopoietic Progenitors from Human Pluripotent Stem Cells
    14:37

    Directed Differentiation of Primitive and Definitive Hematopoietic Progenitors from Human Pluripotent Stem Cells

    Published on: November 1, 2017

    11.8K
    Generic Protocol for Optimization of Heterologous Protein Production Using Automated Microbioreactor Technology
    06:24

    Generic Protocol for Optimization of Heterologous Protein Production Using Automated Microbioreactor Technology

    Published on: December 15, 2017

    10.7K
    A Quantitative Fitness Analysis Workflow
    11:39

    A Quantitative Fitness Analysis Workflow

    Published on: August 13, 2012

    14.9K

    Area of Science:

    • Computer Vision
    • Geometric Modeling
    • 3D Reconstruction

    Background:

    • Detecting 3D primitives in cluttered point clouds is challenging.
    • Existing methods often require pre-segmentation or type specification.
    • Unified representation of various primitives is needed.

    Purpose of the Study:

    • To develop a novel method for detecting 3D primitives in unorganized point clouds.
    • To achieve generic, cross-type, multi-object primitive detection without segmentation.
    • To improve efficiency and accuracy in complex 3D scenes.

    Main Methods:

    • Utilizing quadric surfaces for a unified representation of primitives (planes, spheres, ellipsoids, cones, cylinders, etc.).
    • Developing two novel quadric fitting methods using tangent space information and aligning quadric gradients with surface normals.
    • Implementing a local Hough voting scheme combined with RANSAC for efficient detection, reducing complexity to O(N^3).

    Main Results:

    • The proposed method accurately detects multiple primitive types in cluttered scenes without prior segmentation.
    • The two quadric fitting formulations offer trade-offs between accuracy and computational cost.
    • The Hough voting and RANSAC combination significantly reduces detection complexity.

    Conclusions:

    • This is the first method for generic cross-type multi-object primitive detection in challenging scenes without segmentation.
    • The approach is efficient, flexible, and accurate for 3D point cloud analysis.
    • Quadric surfaces provide a powerful unified framework for primitive representation.