skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


  • Home
  • Search Results
  • Page 1 of 1

Search for: All records

Creators/Authors contains: "Allison, Noah Riley"

Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher. Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?

Some links on this page may take you to non-federal websites. Their policies may differ from this site.

  1. ; ; ; ; (, Journal of The Electrochemical Society)
    Development in the field of gas sensors has witnessed exponential growth with multitude of applications. The diverse applications have led to unexpected challenges. Recent advances in data science have addressed the challenges such as selectivity, drift, aging, limit of detection, and response time. The incorporation of modern data analysis including machine learning techniques have enabled a self-sustaining gas sensing infrastructure without human intervention. This article provides a birds-eye view on data enabled technologies in the realm of gas sensors. While elaborating the prior developments in gas sensing related data analysis, this article is poised to be an entrant for enthusiast in the domain of data science and gas sensors. 
    more » « less
    Full Text Available 
  2. ; ; ; ; ; (, Progress In Electromagnetics Research B)
    Full Text Available