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

Vector Algebra: Graphical Method01:10

Vector Algebra: Graphical Method

15.2K
Vectors can be multiplied by scalars, added to other vectors, or subtracted from other vectors. The vector sum of two (or more) vectors is called the resultant vector or, for short, the resultant.
We use the laws of geometry to construct resultant vectors, followed by trigonometry to find vector magnitudes and directions. For a geometric construction of the sum of two vectors in a plane, we follow the parallelogram rule. Suppose two vectors are at arbitrary positions. Translate either one of...
15.2K
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

140
Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
140
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

786
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
786
Curvilinear Motion: Rectangular Components01:23

Curvilinear Motion: Rectangular Components

738
Curvilinear motion characterizes the movement of a particle or object along a curved path, notably evident when envisioning a car navigating a winding road. If the car starts at point A, its position vector is established within a fixed frame of reference, where the ratio of the position vector to its magnitude signifies the unit vector pointing in the position vector's direction.
As the car advances, its position evolves over time. Quantifying the car's velocity involves computing the...
738
Multicompartment Models: Overview01:14

Multicompartment Models: Overview

283
Multicompartment models are mathematical constructs that depict how drugs are distributed and eliminated within the body. They segment the body into several compartments, symbolizing various physiological or anatomical areas connected through drug transfer processes such as absorption, metabolism, distribution, and elimination.
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
283
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

193
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
193

You might also read

Related Articles

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

Sort by
Same author

OASL knockdown inhibits the progression of stomach adenocarcinoma by regulating the mTORC1 signaling pathway.

FASEB journal : official publication of the Federation of American Societies for Experimental Biology·2023
Same author

Large Piezoelectric Response in a Metal-Free Three-Dimensional Perovskite Ferroelectric.

Journal of the American Chemical Society·2023
Same author

Development of a novel radial-torsional hollow ultrasonic motor and contact interface coating test.

Ultrasonics·2023
Same author

TNFRSF10B is involved in motor dysfunction in Parkinson's disease by regulating exosomal α-synuclein secretion from microglia.

Journal of chemical neuroanatomy·2023
Same author

Photonic sampled and quantized analog-to- digital converters on thin-film lithium niobate platform.

Optics express·2023
Same author

Characterization of the interaction between boscalid and tannic acid and its effect on the antioxidant properties of tannic acid.

Journal of food science·2023
Same journal

HardFlow: Hard-Constrained Sampling for Flow-Matching Models Via Trajectory Optimization.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Industrial Brain: Self-Evolving Neuro-Symbolic Autonomy with Causal Resilience for Cyber-Physical Systems.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Adaptive Hardness-Driven Dictionary Distillation for Incomplete Streaming View Clustering.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Mixture of Global and Local Experts with Diffusion Transformer for Controllable Face Generation.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Task-KV: Task-aware KV Cache Optimization via Semantic Differentiation of Attention Heads.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Achieving Text-based Person Retrieval with Any Granularity.

IEEE transactions on pattern analysis and machine intelligence·2026
See all related articles

Related Experiment Video

Updated: Oct 7, 2025

Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

1.0K

Efficient Variational Bayes Learning of Graphical Models With Smooth Structural Changes.

Hang Yu, Songwei Wu, Justin Dauwels

    IEEE Transactions on Pattern Analysis and Machine Intelligence
    |January 6, 2022
    PubMed
    Summary
    This summary is machine-generated.

    We introduce BASS, a novel Bayesian approach for dynamic graphical models that is computationally efficient and tuning-free. BASS accurately estimates network structures and outperforms existing methods, showing promise in financial and medical applications.

    More Related Videos

    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

    1.3K
    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

    9.3K

    Related Experiment Videos

    Last Updated: Oct 7, 2025

    Constructing and Visualizing Models using Mime-based Machine-learning Framework
    06:19

    Constructing and Visualizing Models using Mime-based Machine-learning Framework

    Published on: July 22, 2025

    1.0K
    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

    1.3K
    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

    9.3K

    Area of Science:

    • Computational Statistics
    • Network Science
    • Machine Learning

    Background:

    • Dynamic undirected graphical models are crucial for analyzing evolving systems in finance, biology, and social sciences.
    • Current methods for learning these models are computationally intensive and require manual tuning of parameters via grid search.
    • Existing approaches face challenges with computational burden and parameter selection, limiting their practical applicability.

    Purpose of the Study:

    • To develop a computationally efficient and tuning-free method for estimating dynamic graphical models.
    • To improve the accuracy and reduce the complexity of learning network structures over time.
    • To extend the applicability of dynamic graphical models to frequency-domain analysis and time series data.

    Main Methods:

    • Proposed BASS (Bayesian Approach for Sparse and Smooth dynamic graphical models), a tuning-free Bayesian method.
    • Utilized temporally dependent spike and slab priors for sparse and smooth graph structures.
    • Developed an efficient variational inference algorithm with natural gradients, achieving O(NP^2) time complexity, and incorporated simulated annealing with bootstrapping to address local maxima.

    Main Results:

    • BASS demonstrates superior structure estimation accuracy on synthetic data compared to existing methods, especially for high-dimensional data.
    • Analysis of stock market data revealed network changes coinciding with major financial crises.
    • Application to EEG data showed BASS can effectively distinguish between Alzheimer's patients and healthy controls.

    Conclusions:

    • BASS offers a significant advancement in learning dynamic graphical models, providing a computationally efficient and accurate alternative.
    • The method's flexibility allows for extensions to frequency-varying models and analysis of multivariate time series.
    • BASS shows strong potential for applications in finance, neuroscience, and other fields requiring dynamic network analysis.