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

Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

13.9K
Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
13.9K
Random Sampling Method01:09

Random Sampling Method

11.8K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest. Among the various sampling methods used by...
11.8K
DNA as a Genetic Template02:05

DNA as a Genetic Template

6.9K
6.9K
Next-generation Sequencing03:00

Next-generation Sequencing

92.1K
The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features....
92.1K
Genetic Material01:20

Genetic Material

2.0K
Within the human body, a complex and detailed system of trillions of cells works in unison to sustain life. Each cell houses a nucleus, which contains 46 chromosomes divided into 23 pairs. Chromosomes are highly coiled structures made of the genetic material DNA. These chromosomes are essential carriers of genetic information, with half inherited from the mother through her egg and the other half from the father's sperm, combining to create the unique genetic makeup of an individual.
2.0K
Maxam-Gilbert Sequencing01:05

Maxam-Gilbert Sequencing

11.4K
In the same year as the discovery of the Sanger sequencing method, another group of scientists, Allan Maxam and Walter Gilbert, demonstrated their chemical-cleavage method for DNA sequencing. The Maxam-Gilbert method relies on using different chemicals that can cleave the DNA sequence at specific sites, the separation of resulting DNA fragments of variable size using electrophoresis, and deciphering the DNA sequence from the resulting gel bands.
Challenges of the Maxam-Gilbert Method
The...
11.4K

You might also read

Related Articles

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

Sort by
Same author

Empirical Evaluation of an Elitist Replacement Strategy for Differential Evolution with Micro-Populations.

Biomimetics (Basel, Switzerland)·2025
Same author

Parkinson's Disease Detection from Voice Recordings Using Associative Memories.

Healthcare (Basel, Switzerland)·2023
Same author

Path Planning Generator with Metadata through a Domain Change by GAN between Physical and Virtual Environments.

Sensors (Basel, Switzerland)·2021
Same author

Hand Movement Classification Using Burg Reflection Coefficients.

Sensors (Basel, Switzerland)·2019
Same author

An Associative Memory Approach to Healthcare Monitoring and Decision Making.

Sensors (Basel, Switzerland)·2018
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

Related Experiment Video

Updated: Aug 17, 2025

Isolation of Next-Generation Gene Therapy Vectors through Engineering, Barcoding, and Screening of Adeno-Associated Virus AAV Capsid Variants
09:20

Isolation of Next-Generation Gene Therapy Vectors through Engineering, Barcoding, and Screening of Adeno-Associated Virus AAV Capsid Variants

Published on: October 18, 2022

4.7K

Path Generator with Unpaired Samples Employing Generative Adversarial Networks.

Javier Maldonado-Romo1,2, Alberto Maldonado-Romo3, Mario Aldape-Pérez2

  • 1Institute of Advanced Materials and Sustainable Manufacturing, Tecnologico de Monterrey, Mexico City 14380, Mexico.

Sensors (Basel, Switzerland)
|December 11, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces a novel method for real-time path generation on smartphones using unpaired data, enabling augmented reality experiences without costly sensors. The approach effectively navigates physical spaces by avoiding virtual objects, even with limited environmental knowledge.

Keywords:
machine learningneural networkspath generatorunpaired datasets

More Related Videos

Using Generative Art to Convey Past and Future Climate Transitions
06:10

Using Generative Art to Convey Past and Future Climate Transitions

Published on: March 31, 2023

1.0K
Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
04:48

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

480

Related Experiment Videos

Last Updated: Aug 17, 2025

Isolation of Next-Generation Gene Therapy Vectors through Engineering, Barcoding, and Screening of Adeno-Associated Virus AAV Capsid Variants
09:20

Isolation of Next-Generation Gene Therapy Vectors through Engineering, Barcoding, and Screening of Adeno-Associated Virus AAV Capsid Variants

Published on: October 18, 2022

4.7K
Using Generative Art to Convey Past and Future Climate Transitions
06:10

Using Generative Art to Convey Past and Future Climate Transitions

Published on: March 31, 2023

1.0K
Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
04:48

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

480

Area of Science:

  • Computer Science
  • Human-Computer Interaction
  • Robotics

Background:

  • Interactive technologies like augmented reality (AR) demand significant computational power and specialized sensors for real-time immersive experiences, leading to high implementation costs.
  • Machine learning offers cost-reduction potential but faces challenges due to the complexity of creating comprehensive datasets for environmental perception.

Purpose of the Study:

  • To propose an alternative strategy for real-time path generation on embedded devices using limited, unpaired environmental data.
  • To enable augmented reality experiences that can navigate physical spaces by avoiding virtual elements, even with imperfect environmental knowledge.

Main Methods:

  • Utilized unpaired samples from known and unknown surroundings to generate navigation paths.
  • Developed an architecture for path creation based on imperfect environmental knowledge.
  • Integrated the generated path into an augmented reality experience for user testing and performance evaluation.

Main Results:

  • Successfully approximated a navigation path using an unpaired dataset, demonstrating feasibility with limited information.
  • The proposed strategy allows for real-time path generation on devices like smartphones.
  • User testing validated the performance of the augmented reality experience with the generated path.

Conclusions:

  • The primary contribution is the approximation of a path using unpaired data, offering a cost-effective solution for real-time navigation in augmented reality.
  • This method addresses the limitations of high costs and complex dataset creation in current interactive technologies.
  • The research paves the way for more accessible and efficient augmented reality applications on mobile devices.