Výsledky vyhledávání - "Nathan Phelps"

Akademický článek

An exploratory clustering analysis of the 2016 National Financial Well-Being Survey.

Autor: Nathan Phelps, Adam Metzler

Publikováno v: PLoS ONE, Vol 19, Iss 9, p e0309260 (2024)

This paper uses cluster analysis to explore the results of the 2016 National Financial Well-Being survey. Our analysis identifies four groups, two of which have very similar levels of financial well-being but markedly different objective financial si

Externí odkaz: https://doaj.org/article/bbfb169305224295901e2c1b91e9391f

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Akademický článek

Classification of forest fuels in selected fire-prone ecosystems of Alberta, Canada—implications for crown fire behaviour prediction and fuel management

Autor: Nathan Phelps, Jennifer L. Beverly

Publikováno v: Annals of Forest Science, Vol 79, Iss 1, Pp 1-18 (2022)

Abstract Key message We used clustering to construct fuel classes from fuel inventory data based on three stand attributes relevant to crown fire behaviour: surface fuel load (SFL), canopy base height (CBH) and canopy bulk density (CBD). Resulting fu

Externí odkaz: https://doaj.org/article/600f1fe06e4641d492d4bbd49e96b087

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Akademický článek

The Alberta Wildland Fuels Inventory Program (AWFIP): data description and reference tables

Autor: Nathan Phelps, Hilary Cameron, Air M. Forbes, Tom Schiks, Dave Schroeder, Jennifer L. Beverly

Publikováno v: Annals of Forest Science, Vol 79, Iss 1, Pp 1-16 (2022)

Key message This document describes a dataset obtained from a field sampling program conducted in Alberta, Canada. Field data were used to describe the structure and composition of forest stands, including several fuel loads (e.g., surface, understor

Externí odkaz: https://doaj.org/article/188d90fbc7894117939b8199934873cb

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Akademický článek

Development of a convolutional neural network to differentiate among the etiology of similar appearing pathological B lines on lung ultrasound: a deep learning study

Autor: Thamer Alaifan, Robert Arntfield, Blake VanBerlo, Nathan Phelps, Matthew White, Rushil Chaudhary, Jordan Ho, Derek Wu

Publikováno v: BMJ Open, Vol 11, Iss 3 (2021)

Objectives Lung ultrasound (LUS) is a portable, low-cost respiratory imaging tool but is challenged by user dependence and lack of diagnostic specificity. It is unknown whether the advantages of LUS implementation could be paired with deep learning (

Externí odkaz: https://doaj.org/article/df12b05c6f204c1a802b9ad48f4f6f00

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Comparing calibrated statistical and machine learning methods for wildland fire occurrence prediction: a case study of human-caused fires in Lac La Biche, Alberta, Canada

Autor: Nathan Phelps, Douglas G. Woolford

Publikováno v: International Journal of Wildland Fire. 30:850-870

Wildland fire occurrence prediction (FOP) modelling supports fire management decisions, such as suppression resource pre-positioning and the routeing of detection patrols. Common empirical modelling methods for FOP include both model-based (statistic

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::7eae851d1eca165541ed2a07b9a8af26
https://doi.org/10.1071/wf20139

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Development of a convolutional neural network to differentiate among the etiology of similar appearing pathological B lines on lung ultrasound: a deep learning study

Autor: Robert Arntfield, Thamer Alaifan, Blake VanBerlo, Nathan Phelps, Rushil Chaudhary, Matthew White, Jordan Ho, Derek Wu

Publikováno v: BMJ Open
BMJ Open, Vol 11, Iss 3 (2021)

ObjectivesLung ultrasound (LUS) is a portable, low-cost respiratory imaging tool but is challenged by user dependence and lack of diagnostic specificity. It is unknown whether the advantages of LUS implementation could be paired with deep learning (D

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8c6d795f67096996f766722abb0594bb
http://europepmc.org/articles/PMC7939003

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Development of a deep learning classifier to accurately distinguish COVID-19 from look-a-like pathology on lung ultrasound

Autor: Robert Arntfield, Matthew White, Rushil Chaudhary, Thamer Alaifan, Derek Wu, Blake VanBerlo, Jordan Ho, Nathan Phelps

ObjectivesLung ultrasound (LUS) is a portable, low cost respiratory imaging tool but is challenged by user dependence and lack of diagnostic specificity. It is unknown whether the advantages of LUS implementation could be paired with deep learning te

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::3aa7e064fd86199ed135c9da2e936c6d
https://doi.org/10.1101/2020.10.13.20212258

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Guidelines for effective evaluation and comparison of wildland fire occurrence prediction models

Autor: Nathan Phelps, Douglas G. Woolford

Publikováno v: International Journal of Wildland Fire. 30:225

Daily, fine-scale spatially explicit wildland fire occurrence prediction (FOP) models can inform fire management decisions. Many different data-driven modelling methods have been used for FOP. Several studies use multiple modelling methods to develop

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::c2c20275aabc3de68fece6182dd4e734
https://doi.org/10.1071/wf20134

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