Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Multimachine Stability

Multimachine Stability

Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:

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

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

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...

Associative Learning

Associative Learning

Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
Classical conditioning, also known...

Causes of Similarity-Dissimilarity Effect

Causes of Similarity-Dissimilarity Effect

The similarity-dissimilarity effect, a fundamental concept in social psychology, explains how interpersonal similarities and differences influence attraction and social interactions. This effect is supported by three key psychological perspectives: balance theory, social comparison theory, and consensual validation.Balance Theory and Cognitive ConsistencyBalance theory, developed by Fritz Heider, posits that individuals seek cognitive consistency in their relationships. When two people share...

Multi-input and Multi-variable systems

Multi-input and Multi-variable systems

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 of...

Multicompartment Models: Overview

Multicompartment Models: Overview

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,...

You might also read

Related Articles

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

Sort by

Same author

Dietary <i>Lactobacillus plantarum</i> Supplementation Improves Growth Performance and Antioxidant Status and Upregulates Genes Related to the Toll/Imd and JAK-STAT Signaling Pathways in Red Claw Crayfish (<i>Cherax quadricarinatus</i>).

Animals : an open access journal from MDPI·2026

Same author

Impact of Dietary <i>Lactobacillus plantarum</i> on Muscle Composition, Hemolymph Biochemistry, Lipid Metabolism, and the mTOR Signaling Pathway in Red Claw Crayfish (<i>Cherax quadricarinatus</i>).

Animals : an open access journal from MDPI·2026

Same author

Efficacy and Safety of Adjunctive Cenobamate in Chinese Participants with Focal Seizure.

Advances in therapy·2025

Same author

<i>Rhodotorula mucilaginosa</i> Supplementation Could Significantly Affect the Growth Performance, Digestive Enzyme Activity, Antioxidant Capacity, Immune Function, and Intestinal Health in Red Claw Crayfish (<i>Cherax quadricarinatus</i>).

Biology·2025

Same author

Effects of Dietary <i>Rhodotorula mucilaginosa</i> on Muscle Composition, Serum Biochemical Indicators, Antioxidant Capacity, Lipid Metabolism, and mTOR Signaling Pathway in Red Claw Crayfish (<i>Cherax quadricanatus</i>).

Biology·2025

Same author

Effects of Mannan Oligosaccharides on Growth, Antioxidant and Immune Performance, and mTOR Signaling Pathway in Juvenile Tilapia (<i>Oreochromis niloticus</i>).

Animals : an open access journal from MDPI·2025

Same journal

Strategic Ability Updating in Concurrent Games by Coalitional Commitment.

IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society·2015

Same journal

Meta-Analysis of the First Facial Expression Recognition Challenge.

IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society·2012

Same journal

Adjustable model-based fusion method for multispectral and panchromatic images.

IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society·2012

Same journal

Face Feature Weighted Fusion Based on Fuzzy Membership Degree for Video Face Recognition.

IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society·2012

Same journal

A New Adaptive Fast Cellular Automaton Neighborhood Detection and Rule Identification Algorithm.

IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society·2012

Same journal

Human-arm-and-hand-dynamic model with variability analyses for a stylus-based haptic interface.

IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society·2012

See all related articles

Search research articles

Related Experiment Videos

Learning similarity with multikernel method.

Yi Tang¹, Luoqing Li, Xuelong Li

¹Key Laboratory of Applied Mathematics, Hubei Province, and Faculty of Mathematics and Computer Science, Hubei University, Wuhan 430062, China.

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society

|June 4, 2010

Summary

This summary is machine-generated.

This study introduces a multikernel method to learn pattern similarity by measuring angles in a Hilbert space. The approach, equivalent to learning normalized kernels, yields an effective boosting-style algorithm for similarity learning.

Related Experiment Videos

Area of Science:

Machine Learning
Kernel Methods
Pattern Recognition

Background:

Learning and representing similarity is crucial in machine learning.
Existing methods may not fully capture complex similarity relationships.

Purpose of the Study:

To propose a novel multikernel method for learning similarity.
To establish a theoretical foundation and develop an effective algorithm for similarity learning.

Main Methods:

Measuring pattern similarity using the included angle in a kernel-induced Hilbert space.
Representing similarity via normalized kernels.
Developing a boosting-style algorithm based on an error bound.

Main Results:

Demonstrated that learning similarity is equivalent to learning a normalized kernel.
Established an error bound for the multikernel similarity learning method.
Preliminary experiments validated the effectiveness of the developed algorithm.

Conclusions:

The proposed multikernel method provides a robust framework for learning similarity.
The developed boosting-style algorithm is effective for practical similarity learning tasks.