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

Fault Types

Fault Types

When analyzing a single line-to-ground fault from phase A to ground at a three-phase bus, it is important to consider the fault impedance. This impedance is zero for a bolted fault, equal to the arc impedance for an arcing fault, and represents the total fault impedance for a transmission-line insulator flashover. To derive sequence and phase currents, fault conditions are translated from the phase domain to the sequence domain.
For line-to-line faults occurring between phases B and C, the...

Pharmacodynamic Models: Link Model and Systems Pharmacodynamic Model

Pharmacodynamic Models: Link Model and Systems Pharmacodynamic Model

The link model is a fundamental pharmacokinetic-pharmacodynamic (PK–PD) approach to account for delayed drug responses when the observed effect does not immediately correlate with the drug's plasma concentration peak. This delay is mathematically addressed by introducing an effect compartment concentration, Ce, which is kinetically linked to the plasma concentration, Cp, via a first-order rate constant, ke0. The linkage allows for a more accurate prediction of drug effects over time. A higher...

Ligand Binding and Linkage

Ligand Binding and Linkage

Allosteric proteins have more than one ligand binding site; the binding of a ligand to any of these sites influences the binding of ligands to the other sites. When a protein is allosteric, its binding sites are called coupled or linked. In the case of enzymes, the site that binds to the substrate is known as the active site and the other site is known as the regulatory site. When a ligand binds to the regulatory site, this leads to conformational changes in the protein that can influence the...

Ligand Binding and Linkage

Ligand Binding and Linkage

Allosteric proteins have more than one ligand binding site; the binding of a ligand to any of these sites influences the binding of ligands to the other sites. When a protein is allosteric, its binding sites are called coupled or linked. In the case of enzymes, the site that binds to the substrate is known as the active site and the other site is known as the regulatory site. When a ligand binds to the regulatory site, this leads to conformational changes in the protein that can influence the...

Structural Classification of Joints

Structural Classification of Joints

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...

Design Example: Alignment of a Road Line Using GIS

Design Example: Alignment of a Road Line Using GIS

The alignment of a road line using Geographic Information Systems (GIS) is a critical process in civil engineering, combining advanced technology with practical decision-making. This methodology begins with the collection of geospatial data, including information on land cover, geomorphology, drainage patterns, slope, and contour details. Such data is typically acquired through satellite imagery and GIS tools, offering a comprehensive understanding of the terrain.Once the data is gathered, it...

You might also read

Related Articles

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

Sort by

Same author

The future of fundamental science led by generative closed-loop artificial intelligence.

Frontiers in artificial intelligence·2026

Same author

Improving biomedical entity linking with generative relevance feedback.

Bioinformatics (Oxford, England)·2026

Same author

Desiderata for a biomedical knowledge network: opportunities, challenges and future Directions.

ArXiv·2025

Same author

Atlantification drives recent strengthening of the Arctic overturning circulation.

Science advances·2025

Same author

Biological databases in the age of generative artificial intelligence.

Bioinformatics advances·2025

Same author

Hypothesizing mechanistic links between microbes and disease using knowledge graphs.

bioRxiv : the preprint server for biology·2023

Search research articles

Related Experiment Videos

A fault model for ontology mapping, alignment, and linking systems.

Helen L Johnson¹, K Bretonnel Cohen, Lawrence Hunter

¹Center for Computational Pharmacology, School of Medicine, University of Colorado, Aurora, CO 80045, USA. Helen.Johnson@uchsc.edu

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing

|November 10, 2007

Summary

A new fault model provides a consistent way to evaluate ontology mapping systems. This method helps identify specific errors and suggests improvements for better system performance.

Related Experiment Videos

Area of Science:

Bioinformatics
Ontology Engineering
Natural Language Processing

Background:

Extensive research exists on mapping, alignment, and linking of ontologies (MALO).
However, a significant gap remains in the evaluation methodologies for MALO systems.
Existing evaluation methods lack the granularity needed for detailed system analysis.

Purpose of the Study:

To propose a novel fault model for fine-grained evaluation of MALO systems.
To demonstrate the applicability of this fault model using a specific MALO system.
To identify areas for improvement in current MALO system development.

Main Methods:

Development of a fault model for categorizing errors in MALO systems.
Application of the fault model by two independent judges to a specific MALO system.
Calculation of inter-judge agreement to assess model consistency.

Main Results:

The proposed fault model demonstrated consistent applicability with 98% inter-judge agreement after dispute resolution.
Application of the model successfully explained previously puzzling results from prior work.
Specific areas for MALO system enhancement were identified.

Conclusions:

The proposed fault model offers a reliable and consistent method for evaluating MALO systems.
The model's application revealed key insights into system performance and error sources.
Recommendations include developing domain-specific NLP tools, filtering high-frequency matches, and implementing word sense disambiguation for improved MALO systems.