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

IP3/DAG Signaling Pathway

IP3/DAG Signaling Pathway

Membrane lipids such as phosphatidylinositol (PI) are precursors for several membrane-bound and soluble second messengers. Specific kinases phosphorylate PI and produce phosphorylated inositol phospholipids. One such inositol phospholipids are the phosphatidylinositol-4,5 bisphosphate [PI(4,5)P2], present in the inner half of the lipid bilayer. Upon ligand binding, GPCR stimulates Gq proteins to turn on phospholipase Cꞵ. Activated phospholipase Cꞵ cleaves PI(4,5)P2 and...

Sequence Networks of Rotating Machines

Sequence Networks of Rotating Machines

A Y-connected synchronous generator, grounded through a neutral impedance, is designed to produce balanced internal phase voltages with only positive-sequence components. The generator's sequence networks include a source voltage that is exclusively in the positive-sequence network. The sequence components of line-to-ground voltages at the generator terminals illustrate this configuration.
Zero-sequence current induces a voltage drop across the generator's neutral impedance and other...

You might also read

Related Articles

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

Sort by

Same author

Dietary Fat and Fiber Divergently Control Intestinal Nanoplastic Bioaccumulation through Gut Motility and Barrier Pathways.

Environmental science & technology·2026

Same author

Ecotype-Specific Drilosphere Microbiome Reprogramming Influencing Microplastic Impacts on Soil Carbon-Nitrogen Characteristics and Earthworm Health.

Environmental science & technology·2026

Same author

Development and Validation of an Interpretable Machine Learning Model Based on Peripheral Blood Biomarkers for Esophageal Cancer Risk Prediction.

International journal of general medicine·2026

Same author

Shoot-root hormonal coordination and cross-sphere microbiome assembly underpin nanomaterial-induced resistance to rare earth elements in lettuce.

Journal of hazardous materials·2026

Same author

Photochemical reductive coupling of α-keto esters for synthesizing 2,3-diarylated tartaric acid esters.

Organic & biomolecular chemistry·2026

Same author

All-Polyimide-Mediated Liquid Metal Assembly on Aerogels for Breathable and Robust Electronic Skins.

Advanced materials (Deerfield Beach, Fla.)·2026

Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026

Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026

Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026

Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026

Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026

Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

Sensors (Basel, Switzerland)·2026

See all related articles

Search research articles

Related Experiment Video

Updated: May 5, 2026

A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants

A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants

Published on: August 26, 2018

SGK-Net: A Novel Navigation Scene Graph Generation Network.

Wenbin Yang¹, Hao Qiu¹, Xiangfeng Luo¹

¹School of Computer Engineering and Science, Shanghai University, Shanghai 200444, China.

Sensors (Basel, Switzerland)

|July 13, 2024

Summary

This summary is machine-generated.

This study introduces SGK-Net for navigation scene graph generation (NSGG), improving ship understanding in complex maritime environments. The novel network effectively reduces noise and enhances relationship feature accuracy for safer intelligent navigation.

Keywords:

graph structure learning message passing multimodal fusion navigation scene graph generation

More Related Videos

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

Modeling the Functional Network for Spatial Navigation in the Human Brain

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

Related Experiment Videos

Last Updated: May 5, 2026

A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants

A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants

Published on: August 26, 2018

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

Modeling the Functional Network for Spatial Navigation in the Human Brain

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

Area of Science:

Computer Vision
Artificial Intelligence
Maritime Technology

Background:

Intelligent ships require advanced scene understanding for navigation.
Current navigation scene graph generation (NSGG) faces challenges due to complex relationships and noisy contextual information.
Existing methods struggle with semantic ambiguity and computational complexity in NSGG.

Purpose of the Study:

To propose a novel network, SGK-Net, for enhanced navigation scene graph generation (NSGG).
To address challenges in fusing multimodal information and refining relationship features in navigation scenes.
To introduce the first Ship Navigation Scene Graph Simulation dataset (SNSG-Sim) for research.

Main Methods:

Developed SGK-Net with three modules: Semantic-Guided Multimodal Fusion (SGMF), Graph Structure Learning-based Structure Evolution (GSLSE), and Key Entity Message Passing (KEMP).
SGMF fuses multimodal data using relationship semantics to clarify entity connections.
GSLSE optimizes relationship features using graph structure learning, and KEMP refines features by focusing on key entities to reduce noise.

Main Results:

SGK-Net demonstrated significant improvements on the SNSG-Sim dataset.
Achieved an 8.31% (R@50) increase in the PredCls task and a 7.94% (R@50) increase in the SGCls task compared to baseline methods.
The proposed method effectively reduces semantic ambiguity and noise interference.

Conclusions:

SGK-Net significantly advances the field of navigation scene graph generation.
The developed network architecture and the SNSG-Sim dataset provide valuable contributions to intelligent ship navigation research.
The findings validate the effectiveness of the proposed modules in handling complex navigation scene data.