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

Classification of Systems-II01:31

Classification of Systems-II

343
Continuous-time systems have continuous input and output signals, with time measured continuously. These systems are generally defined by differential or algebraic equations. For instance, in an RC circuit, the relationship between input and output voltage is expressed through a differential equation derived from Ohm's law and the capacitor relation,
343
Classification of Systems-I01:26

Classification of Systems-I

424
Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
424
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

167
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
167
Residuals and Least-Squares Property01:11

Residuals and Least-Squares Property

8.3K
The vertical distance between the actual value of y and the estimated value of y. In other words, it measures the vertical distance between the actual data point and the predicted point on the line
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...
8.3K
State Space Representation01:27

State Space Representation

359
The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
Consider an RLC circuit, a...
359
Structural Classification of Joints01:20

Structural Classification of Joints

6.1K
Joints, also known as articulations, are classified based on their structural characteristics, i.e., based on whether the articulating surfaces of the adjacent bones are directly connected by fibrous connective tissue or cartilage, or whether the articulating surfaces contact each other within a fluid-filled joint cavity. These differences serve to divide the joints of the body into three structural classifications.
A fibrous joint is where the adjacent bones are united by fibrous connective...
6.1K

You might also read

Related Articles

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

Sort by
Same author

Habitat heterogeneity analysis of planning CT improves the prediction of radiation proctitis in cervical cancer: A multimodal machine learning study.

Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine·2026
Same author

LAD/BSA and NT-proBNP as predictors of cardiovascular death in pediatric left ventricular non-compaction: a multicenter longitudinal cohort study.

Pediatric research·2026
Same author

Work engagement and associated factors of nurses: a structural equation model.

Frontiers in psychology·2026
Same author

Vertical profile of ambient VOCs in background region of Southwest China from Mt. Fanjing observation.

Scientific reports·2026
Same author

The quintom theory of dark energy after DESI DR2.

National science review·2026
Same author

Dynamic maps of plastic-mulched farmlands in Northeast China from 1985 to 2025.

Scientific data·2026

Related Experiment Video

Updated: Nov 12, 2025

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines
08:27

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

Published on: January 5, 2024

1.4K

Hessian Semisupervised Scatter Regularized Classification Model With Geometric and Discriminative Information for

Chihang Wei, Liyun Zuo, Xinmin Zhang

    IEEE Transactions on Cybernetics
    |March 17, 2021
    PubMed
    Summary

    This study introduces a novel Hessian semisupervised scatter regularized classification model. This advanced method effectively utilizes both labeled and unlabeled data for accurate nonlinear process classification.

    More Related Videos

    Optical Scatter Microscopy Based on Two-Dimensional Gabor Filters
    14:58

    Optical Scatter Microscopy Based on Two-Dimensional Gabor Filters

    Published on: June 2, 2010

    9.8K
    Visualization Method for Proprioceptive Drift on a 2D Plane Using Support Vector Machine
    07:05

    Visualization Method for Proprioceptive Drift on a 2D Plane Using Support Vector Machine

    Published on: October 27, 2016

    9.4K

    Related Experiment Videos

    Last Updated: Nov 12, 2025

    Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines
    08:27

    Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

    Published on: January 5, 2024

    1.4K
    Optical Scatter Microscopy Based on Two-Dimensional Gabor Filters
    14:58

    Optical Scatter Microscopy Based on Two-Dimensional Gabor Filters

    Published on: June 2, 2010

    9.8K
    Visualization Method for Proprioceptive Drift on a 2D Plane Using Support Vector Machine
    07:05

    Visualization Method for Proprioceptive Drift on a 2D Plane Using Support Vector Machine

    Published on: October 27, 2016

    9.4K

    Area of Science:

    • Machine Learning
    • Data Science
    • Process Engineering

    Background:

    • Semisupervised learning and discriminative information are crucial for classification.
    • Existing methods have not fully integrated these approaches for nonlinear processes.
    • Efficiently utilizing labeled and unlabeled data remains a challenge.

    Purpose of the Study:

    • To propose a coherent framework for nonlinear process classification using semisupervised and discriminative information.
    • To develop a model that leverages both labeled and unlabeled data effectively.
    • To enhance classification accuracy in complex industrial processes.

    Main Methods:

    • Developed the Hessian semisupervised scatter regularized classification model.
    • Incorporated a loss function for accuracy evaluation.
    • Included regularization terms for geometry, discriminative information, and model complexity.
    • Considered both reproducing kernel Hilbert space and linear space formulations.

    Main Results:

    • The proposed model achieves theoretically guaranteed analytical solutions in both Hilbert and linear spaces.
    • Experimental results on a benchmark dataset and an industrial polyethylene process demonstrate high accuracy.
    • The method accurately predicts class information for newly collected data.

    Conclusions:

    • The Hessian semisupervised scatter regularized classification model offers a robust framework for nonlinear process classification.
    • The integration of semisupervised and discriminative techniques significantly improves classification performance.
    • This approach provides a valuable tool for analyzing and classifying complex industrial data.