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

Precipitation and Co-precipitation

Precipitation and Co-precipitation

Precipitation and coprecipitation methods can be used to separate a mixture of ions in a solution. In qualitative inorganic analysis, ions that form sparingly soluble precipitates with the same reagent are separated based on the differences in solubility products. For example, consider the separation of Cu(II) and Fe(II) ions by precipitation as insoluble sulfides. First, copper(II) sulfide is precipitated by the addition of acidic H2S, where the dissociation of H2S is suppressed. Adding H2S...

Precipitation Processes

Precipitation Processes

The experimental conditions in a gravimetric analysis should be optimized to maximize the particle size and purity of the obtained precipitate. Ideally, the concentration of the precipitating reagent should be low with effective stirring to maintain low relative supersaturation for the growth of large crystals. In homogeneous precipitation, the precipitant is slowly generated by a chemical reaction in the solution to avoid local reagent excesses. For example, urea decomposes gradually to...

Variation of Atmospheric Pressure

Variation of Atmospheric Pressure

Change in atmospheric pressure with height is particularly interesting. The decrease in atmospheric pressure with increasing altitude is due to the decreasing gravitational force per unit area as we move away from the surface of the earth.
Assuming the air temperature is constant at a given altitude and that the ideal gas law of thermodynamics describes the atmosphere to a good approximation, one can find the variation of atmospheric pressure with height.
Let p(y) be the atmospheric pressure at...

Attenuated Total Reflectance (ATR) Infrared Spectroscopy: Overview

Attenuated Total Reflectance (ATR) Infrared Spectroscopy: Overview

Attenuated total reflectance (ATR) infrared spectroscopy is a powerful analytical technique used to study the composition of materials. It is widely employed in chemistry, materials science, forensic science, and other fields where sample characterization is required. ATR has several advantages over traditional transmission IR spectroscopy, including the requirement of little to no sample preparation and the ability to analyze a wide range of samples.
The ATR process begins by directing a beam...

Boundary Layer Characteristics

Boundary Layer Characteristics

When a fluid encounters a solid surface, a boundary layer forms due to the interaction between the fluid's motion and the stationary surface. This phenomenon is characterized by a thin region adjacent to the surface where viscous forces dominate, influencing the fluid's velocity profile. The development of the boundary layer begins at the leading edge of the surface and evolves as the fluid moves downstream.As the fluid flows over the surface, friction between the fluid and the wall slows down...

You might also read

Related Articles

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

Sort by

Same author

YOLO-ERCD: An Upgraded YOLO Framework for Efficient Road Crack Detection.

Sensors (Basel, Switzerland)·2026

Same author

Advancing Biomechanics-Based Motion Analysis from Methodology to Application.

Bioengineering (Basel, Switzerland)·2025

Same author

Biomechanics and Motion Analysis: From Human Performance to Clinical Practice.

Bioengineering (Basel, Switzerland)·2025

Same author

Determining post-orthognathic surgery profile: A validation study on the potential of modified chin point as a reliable predictor.

PloS one·2025

Same author

Evaluation of Chatbot Responses to Text-Based Multiple-Choice Questions in Prosthodontic and Restorative Dentistry.

Dentistry journal·2025

Same author

Meteorological Visibility Estimation Using Landmark Object Extraction and the ANN Method.

Sensors (Basel, Switzerland)·2025

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: Mar 29, 2026

Methods to Test Visual Attention Online

Methods to Test Visual Attention Online

Published on: February 19, 2015

A Range-Aware Attention Framework for Meteorological Visibility Estimation.

Wai Lun Lo¹, Kwok Wai Wong¹, Richard Tai Chiu Hsung¹

¹Department of Computer Science, Hong Kong Chu Hai College, Hong Kong, China.

Sensors (Basel, Switzerland)

|March 28, 2026

Summary

This summary is machine-generated.

This study introduces a new dataset and a Range-Aware Attention Framework (RAT-Attn) for accurate meteorological visibility estimation. The framework improves deep learning models

Keywords:

artificial neural network deep learning hybrid architecture meteorological visibility estimation

More Related Videos

A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers

A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers

Published on: January 18, 2020

Investigating the Deployment of Visual Attention Before Accurate and Averaging Saccades via Eye Tracking and Assessment of Visual Sensitivity

Investigating the Deployment of Visual Attention Before Accurate and Averaging Saccades via Eye Tracking and Assessment of Visual Sensitivity

Published on: March 18, 2019

Related Experiment Videos

Last Updated: Mar 29, 2026

Methods to Test Visual Attention Online

Methods to Test Visual Attention Online

Published on: February 19, 2015

A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers

A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers

Published on: January 18, 2020

Investigating the Deployment of Visual Attention Before Accurate and Averaging Saccades via Eye Tracking and Assessment of Visual Sensitivity

Investigating the Deployment of Visual Attention Before Accurate and Averaging Saccades via Eye Tracking and Assessment of Visual Sensitivity

Published on: March 18, 2019

Area of Science:

Meteorology
Computer Vision
Artificial Intelligence

Background:

Accurate meteorological visibility estimation is crucial for transportation safety and environmental monitoring.
Current deep learning models face challenges due to non-linear atmospheric visual degradation and limited calibrated datasets.

Purpose of the Study:

To introduce the Hong Kong Chu Hai College Visibility Dataset (HKCHC-VD) with high-resolution images and precise visibility measurements.
To propose a novel Range-Aware Attention Framework (RAT-Attn) for enhanced visibility estimation.

Main Methods:

Developed the HKCHC-VD dataset with 11,148 images and Biral SWS-100 sensor data.
Proposed RAT-Attn, an adaptive attention mechanism integrating CNN and Vision Transformer with a learnable threshold.
Enabled dynamic feature prioritization based on visibility intervals to address non-linear degradation.

Main Results:

The proposed RAT-Attn framework outperformed existing baseline methods.
The ResNet + ViT (spatial-threshold) variant achieved an MSE of 5.87 km², MAE of 1.65 km, and 87.07% classification accuracy.
Reduced regression error by over 75% in critical low-visibility conditions (0-10 km).

Conclusions:

Range-aware adaptive feature fusion is essential for robust meteorological visibility estimation.
The developed dataset and framework offer significant improvements for real-world applications.
The study highlights the potential of domain-specific architectural optimization in deep learning for environmental sensing.